redis streams documentation

More powerful features to consume streams are available using the consumer groups API, however reading via consumer groups is implemented by a different command called XREADGROUP, covered in the next section of this guide. Now it's time to zoom in to see the fundamental consumer group commands. Adding a few million unacknowledged messages to the stream does not change the gist of the benchmark, with most queries still processed with very short latency. They are the following: Assuming I have a key mystream of type stream already existing, in order to create a consumer group I just need to do the following: As you can see in the command above when creating the consumer group we have to specify an ID, which in the example is just $. Learn more about Redis Streams in the Redis reference documentation. Can block. Currently the stream is not deleted even when it has no associated consumer groups, but this may change in the future. This special ID means that we want only entries that were never delivered to other consumers so far. This is what $ means. Redis, meanwhile, recently announced its new data structure, called “ Streams,” for managing streaming data. For instance, if I want to query a two milliseconds period I could use: I have only a single entry in this range, however in real data sets, I could query for ranges of hours, or there could be many items in just two milliseconds, and the result returned could be huge. ... Redis Streams provide read commands that allow consumption of the stream from an arbitrary position (random access) within the known stream content and beyond the stream end to consume new stream … The sequence number is used for entries created in the same millisecond. Although this pattern has similarities to Pub/Sub, the main difference lies in the persistence of messages and … This package wraps XREAD and XADD such tha… This is useful because the consumer may have crashed before, so in the event of a restart we want to re-read messages that were delivered to us without getting acknowledged. However latency becomes an interesting parameter if we want to understand the delay of processing a message, in the context of blocking consumers in a consumer group, from the moment the message is produced via XADD, to the moment the message is obtained by the consumer because XREADGROUP returned with the message. Consumers are auto-created the first time they are mentioned, no need for explicit creation. However, it’s not efficient to replicate every change to a consumer or consumer group. for Dummies, Create and Edit a Cloud Account for Redis Cloud Ultimate, Creating IAM Entities for AWS Cloud Accounts, AWS Zone Mapping for Redis Cloud Essentials, The Processing and Provisioning Lifecycle, Getting Started with Redis Enterprise Software, Getting Started with Redis on Flash (RoF), Getting Started with Redis Enterprise Active-Active Databases, Getting Started with Redis Enterprise Software using Docker, Configuring AWS EC2 instances for Redis Enterprise Software, Setting Up a Cluster Behind a Load Balancer, Database Persistence with Redis Enterprise Software, Geo-Distributed Active-Active Redis Applications, Rack-zone awareness in Redis Enterprise Software, Memory Architecture in Redis Enterprise Software, Memory Management with Redis Enterprise Software, Redis Enterprise Software Compatibility with Open Source Redis, Active-Passive Geo-Distributed Redis (Replica-Of), Private and Public Endpoints on Redis Enterprise Software, Configuring TLS Authentication and Encryption, User Login Lockout for Security Compliance, Creating a Redis Enterprise Software Database, Create an Active-Active Geo-Replicated Database, Create an Active-Passive Geo-Replicated Database, Cluster Name, Email Service, Time Zone, and License, Distributed Synchronization for Replicated Databases, Causal Consistency in an Active-Active Database, Redis Enterprise Software Integration with Prometheus, Redis Enterprise Software Integration with Nagios, Database Metrics Not Collected During Resharding, Redis Enterprise Software Product Lifecycle, Developing Applications with Active-Active Databases, Developing with Hashes in an Active-Active database, Developing with HyperLogLog in an Active-Active database, Developing with Lists in an Active-Active Database, Developing with Sets in an Active-Active database, Developing with Sorted Sets in an Active-Active database, Developing with Strings in an Active-Active database, Benchmark a Redis on Flash Enabled Database, Redis Enterprise Software Release Notes 6.0.8 (September 2020), Redis Enterprise Software Release Notes 6.0 (May 2020), Redis Enterprise Software Release Notes 5.6.0 (April 2020), Redis Enterprise Software Release Notes 5.4.14 (February 2020), Redis Enterprise Software Release Notes 5.4.10 (December 2019), Redis Enterprise Software Release Notes 5.4.6 (July 2019), Redis Enterprise Software Release Notes 5.4.4 (June 2019), Redis Enterprise Software Release Notes 5.4.2 (April 2019), Redis Enterprise Software Release Notes 5.5 Preview (April 2019), Redis Enterprise Software Release Notes 5.4 (December 2018), Redis Enterprise Software 5.2.2 (August 2018), Redis Enterprise Software Release Notes 5.3 BETA (July 2018), Redis Enterprise Software Release Notes 5.2 (June 2018), Redis Enterprise Software 5.0.2 (2018 March), Redis Enterprise Pack 5.0 Release Notes (November 2017), Redis Enterprise Pack 4.5 Release Notes (May 2017), RLEC 4.3.0-230 Release Notes (August 2, 2016), RLEC 4.2.1-30 Release Notes (October 18, 2015), RLEC 4.0.0-49 Release Notes (June 18, 2015), RLEC 0.99.5-24 Release Notes (February 15, 2015), RLEC 0.99.5-11 Release Notes (January 5, 2015), Getting Started with Kubernetes and OpenShift, Getting Started with the OperatorHub on OpenShift 4.x, Getting Started with PKS (Pivotal Container Service), Getting Started with Redis Enterprise Software for Pivotal Platform, Using Redis Enterprise Software on Pivotal Platform, Backup and Restore for Redis Enterprise Software on Pivotal Platform, Getting Started with Redis Enterprise Software using Kubernetes, Redis Enterprise Kubernetes Operator-based Architecture, Managing Redis Enterprise Databases in Kubernetes, Deploying Kubernetes with Persistent Volumes in Operator-based Architecture, Sizing and Scaling a Redis Enterprise Cluster Kubernetes Deployment, Upgrading a Redis Enterprise Cluster in Operator-based Architecture, Redis Enterprise Cluster Recovery for Kubernetes, Redis Enterprise for Kubernetes Release Notes 6.0.8-20 (December 2020), Redis Enterprise for Kubernetes Release Notes 6.0.8-1 (October 2020), Redis Enterprise for Kubernetes Release Notes 6.0.6-24 (August 2020), Redis Enterprise for Kubernetes Release Notes 6.0.6-23 (August 2020), Redis Enterprise for Kubernetes Release Notes 6.0.6-11 (July 2020), Redis Enterprise for Kubernetes Release Notes 6.0.6-6 (June 2020), Redis Enterprise for Kubernetes Release Notes 5.4.10-8 (January 2020), Installing the RedisInsight Desktop Client, Redis Stars This model is push based, since adding data to the consumers buffers will be performed directly by the action of calling XADD, so the latency tends to be quite predictable. The following command shows how to add an entry to a Redis Stream. This is the result of the command execution: The message was successfully claimed by Alice, that can now process the message and acknowledge it, and move things forward even if the original consumer is not recovering. This way, querying using just two milliseconds Unix times, we get all the entries that were generated in that range of time, in an inclusive way. We can check in more detail the state of a specific consumer group by checking the consumers that are registered in the group. Management, Real Time As you can see the "apple" message is not delivered, since it was already delivered to Alice, so Bob gets orange and strawberry, and so forth. A consumer group is like a pseudo consumer that gets data from a stream, and actually serves multiple consumers, providing certain guarantees: In a way, a consumer group can be imagined as some amount of state about a stream: If you see this from this point of view, it is very simple to understand what a consumer group can do, how it is able to just provide consumers with their history of pending messages, and how consumers asking for new messages will just be served with message IDs greater than last_delivered_id. XGROUP SETID and DELCONSUMER are not replicated. Notice that after syncing, both regions have identical streams: Notice also that the synchronized streams contain no duplicate IDs. Before providing the results of performed tests, it is interesting to understand what model Redis uses in order to route stream messages (and in general actually how any blocking operation waiting for data is managed). A payload consisting of a series key-value pairs. To maintain consumer groups in Active-Active databases with optimal performance: Using XREADGROUP across regions can result in regions reading the same entries. Renaming a stream (using RENAME) deletes all consumer group information. If we continue with the analogy of the log file, one obvious way is to mimic what we normally do with the Unix command tail -f, that is, we may start to listen in order to get the new messages that are appended to the stream. Consuming records. Feature overview. If you use N streams with N consumers, so that only a given consumer hits a subset of the N streams, you can scale the above model of 1 stream -> 1 consumer. However in certain problems what we want to do is not to provide the same stream of messages to many clients, but to provide a different subset of messages from the same stream to many clients. However there is a mandatory option that must be always specified, which is GROUP and has two arguments: the name of the consumer group, and the name of the consumer that is attempting to read. An obvious case where this is useful is that of messages which are slow to process: the ability to have N different workers that will receive different parts of the stream allows us to scale message processing, by routing different messages to different workers that are ready to do more work. It offers versatile data structures and simple commands that make it easy for you to build high-performance applications. 130-0 was acknowledged, but not its preceding entries (120-0). After that, we’ll explore the Redis Streams commands in detail, and discover how this new data structure works under the hood. Redis 5 adds Streams, a powerful new data structure which simplifies the construction of real-time applications. The blocking form of XREAD is also able to listen to multiple Streams, just by specifying multiple key names. This way, given a key that received data, we can resolve all the clients that are waiting for such data. However there might be a problem processing some specific message, because it is corrupted or crafted in a way that triggers a bug in the processing code. It may also even return entries that have already been acknowledged. This is the topic of the next section. When we do not want to access items by a range in a stream, usually what we want instead is to subscribe to new items arriving to the stream. The MONITOR CLI command is a debugging command that streams back every command processed by the Redis server. However in the real world consumers may permanently fail and never recover. Redis and the cube logo are registered Streams, on the other hand, are allowed to stay at zero elements, both as a result of using a MAXLEN option with a count of zero (XADD and XTRIM commands), or because XDEL was called. By default the asynchronous replication will not guarantee that. The Stream is a new data type introduced with Redis 5.0, which models a log data structure in a more abstract way. Usually, you should allow Redis streams generate its own stream entry IDs. This specification describes the redis-streams trigger that scales … It should be enough to say that stream commands are at least as fast as sorted set commands when extracting ranges, and that XADD is very fast and can easily insert from half a million to one million items per second in an average machine if pipelining is used. XGROUP CREATE also supports creating the stream automatically, if it doesn't exist, using the optional MKSTREAM subcommand as the last argument: Now that the consumer group is created we can immediately try to read messages via the consumer group using the XREADGROUP command. A stream entry is not just a string, but is instead composed of one or multiple field-value pairs. Streams Consumer Groups provide a level of control that Pub/Sub or blocking lists cannot achieve, with different groups for the same stream, explicit acknowledgment of processed items, ability to inspect the pending items, claiming of unprocessed messages, and coherent history visibility for each single client, that is only able to see its private past history of messages. Note that we might process a message multiple times or one time (at least in the case of consumer failures, but there are also the limits of Redis persistence and replication involved, see the specific section about this topic). However, this also means that it is up to the client to provide a unique identifier. Redis interperts the acknowledgment as: this message was correctly processed so it can be evicted from the consumer group. Structured Streaming, introduced with Apache Spark 2.0, delivers a SQL-like interface for streaming data. A payload consisting of a series key-value pairs. The output of the example above, where the GROUPS subcommand is used, should be clear observing the field names. open source software. Redis consumer groups offer a feature that is used in these situations in order to claim the pending messages of a given consumer so that such messages will change ownership and will be re-assigned to a different consumer. For instance XINFO STREAM reports information about the stream itself. This special ID is only valid in the context of consumer groups, and it means: messages never delivered to other consumers so far. Many applications do not want to collect data into a stream forever. After syncing, the stream x contains two entries with the same ID. Redis Streams is a new feature for Redis 5.0. In traffic redirection, XREADGROUP may return entries that have been read but not acknowledged. Active-Active databases use an “observed-remove” approach to automatically resolve potential conflicts. “StrictRedis” has been renamed to “Redis” and an alias named “StrictRedis” is provided so that users previously using “StrictRedis” can continue to run unchanged. Of course, you can specify any other valid ID. Introduction to Redis Streams. However, the interesting part is that we can turn XREAD into a blocking command easily, by specifying the BLOCK argument: Note that in the example above, other than removing COUNT, I specified the new BLOCK option with a timeout of 0 milliseconds (that means to never timeout). What makes Redis streams the most complex type of Redis, despite the data structure itself being quite simple, is the fact that it implements additional, non mandatory features: a set of blocking operations allowing consumers to wait for new data added to a stream by producers, and in addition to that a concept called Consumer Groups. However, we also provide a minimum idle time, so that the operation will only work if the idle time of the mentioned messages is greater than the specified idle time. If for some reason the user needs incremental IDs that are not related to time but are actually associated to another external system ID, as previously mentioned, the XADD command can take an explicit ID instead of the * wildcard ID that triggers auto-generation, like in the following examples: Note that in this case, the minimum ID is 0-1 and that the command will not accept an ID equal or smaller than a previous one: Now we are finally able to append entries in our stream via XADD. This is, basically, the part which is common to most of the other Redis data types, like Lists, Sets, Sorted Sets and so forth. We could also see a stream in quite a different way: not as a messaging system, but as a time series store. Each stream entry consists of: You add entries to a stream with the XADD command. Each consumer group has the concept of the. This means that the XREADGROUP does not return already-acknowledged entries. Otherwise, the command will block and will return the items of the first stream which gets new data (according to the specified ID). We can ask for more info by giving more arguments to XPENDING, because the full command signature is the following: By providing a start and end ID (that can be just - and + as in XRANGE) and a count to control the amount of information returned by the command, we are able to know more about the pending messages. One is the MAXLEN option of the XADD command. This website is After the sync, at t6, the entry with ID ending in 3700 exists in both regions. However the essence of a log is still intact: like a log file, often implemented as a file open in append only mode, Redis Streams are primarily an append only data structure. Similarly, after a restart, the AOF will restore the consumer groups' state. So XRANGE is also the de facto streams iterator and does not require an XSCAN command. And will increment its number of deliveries counter, so the second client will fail claiming it. We have two messages from Bob, and they are idle for 74170458 milliseconds, about 20 hours. 2. You add entries to a stream with the XADD command. Altering the single macro node, consisting of a few tens of elements, is not optimal. In the above command we wrote STREAMS mystream 0 so we want all the messages in the Stream mystream having an ID greater than 0-0. To change XADD’s ID generation mode, use the rladmin command-line utility: In open source Redis and in non-Active-Active databases, you can use XREAD to iterate over the entries in a Redis Stream. The option COUNT is also supported and is identical to the one in XREAD. As you can see in the example above, the command returns the key name, because actually it is possible to call this command with more than one key to read from different streams at the same time. Stream IDs in open source Redis consist of two integers separated by a dash ('-'). Note how after the STREAMS option we need to provide the key names, and later the IDs. The Ruby code is aimed to be readable by virtually any experienced programmer, even if they do not know Ruby: As you can see the idea here is to start by consuming the history, that is, our list of pending messages. Because we have the counter of the delivery attempts, we can use that counter to detect messages that for some reason are not processable. Implemented Sync & Async methods for all Stream related commands (minus the blocking options) as of 5.0 RC1. Using the traditional terminology we want the streams to be able to fan out messages to multiple clients. The JUSTID option can be used in order to return just the IDs of the message successfully claimed. However, this also means that in Redis if you really want to partition messages in the same stream into multiple Redis instances, you have to use multiple keys and some sharding system such as Redis Cluster or some other application-specific sharding system. Queuing apps such as Celery and Sidekiq could use Streams. Before reading from the stream, let's put some messages inside: Note: here message is the field name, and the fruit is the associated value, remember that stream items are small dictionaries. There is also the XTRIM command, which performs something very similar to what the MAXLEN option does above, except that it can be run by itself: However, XTRIM is designed to accept different trimming strategies, even if only MAXLEN is currently implemented. With this argument, the trimming is performed only when we can remove a whole node. It can be 1000 or 1010 or 1030, just make sure to save at least 1000 items. Normally for an append only data structure this may look like an odd feature, but it is actually useful for applications involving, for instance, privacy regulations. Check out the documentation to learn more. Let’s take a look at how we can use a Redis Stream through redis-cli applying the commands we’ve seen before. A single Redis stream is not automatically partitioned to multiple instances. You access stream entries using the XRANGE, XREADGROUP, and XREAD commands (however, see the caveat about XREAD below). However, with an Active-Active database, XREAD may skip entries. To query the stream by range we are only required to specify two IDs, start and end. You can use XREAD to reliably consume a stream only if all writes to the stream originate from a single region. AOF must be used with a strong fsync policy if persistence of messages is important in your application. We have just to repeat the same ID twice in the arguments. In order to continue the iteration with the next two items, I have to pick the last ID returned, that is 1519073279157-0 and add the prefix ( to it. Redis is an open-source in-memory data store that can serve as a database, cache, message broker, and queue. The two special IDs - and + respectively mean the smallest and the greatest ID possible. In order to check this latency characteristics a test was performed using multiple instances of Ruby programs pushing messages having as an additional field the computer millisecond time, and Ruby programs reading the messages from the consumer group and processing them. Every new ID will be monotonically increasing, so in more simple terms, every new entry added will have a higher ID compared to all the past entries. Redis Keyspace Notifications. However we may want to do more than that, and the XINFO command is an observability interface that can be used with sub-commands in order to get information about streams or consumer groups. This image shows how data is sent to Stream Analytics, analyzed, and sent for other actions like storage, or presentation: A Redis Stream is a data structure that acts like an append-only log. There is currently no option to tell the stream to just retain items that are not older than a given period, because such command, in order to run consistently, would potentially block for a long time in order to evict items. Finally, if we see a stream from the point of view of consumers, we may want to access the stream in yet another way, that is, as a stream of messages that can be partitioned to multiple consumers that are processing such messages, so that groups of consumers can only see a subset of the messages arriving in a single stream. Active-Active databases allow you to write to the same logical stream from more than one region. This way, each entry of a stream is already structured, like an append only file written in CSV format where multiple separated fields are present in each line. This is similar to the tail -f Unix command in some way. In this scenario, two entries with the ID 100-1 are added at t1. Create readable/writeable/pipeable api compatible streams from redis commands.. Let’s add (and initially create a stream) message to a new stream. When the server generates the ID, the first integer is the current time in milliseconds, and the second integer is a sequence number. This is definitely another useful access mode. Using a Redis Stream. The first two special IDs are - and +, and are used in range queries with the XRANGE command. Redis 5.0 introduced Redis Streams which is an append-only log data structure.. One of its features includes Consumer Groups, that allows a group of clients to co-operate consuming a different portion of the same stream of messages.. The system used for this benchmark is very slow compared to today's standards. The counter that you observe in the XPENDING output is the number of deliveries of each message. If the request can be served synchronously because there is at least one stream with elements greater than the corresponding ID we specified, it returns with the results. This makes it much more efficient, and it is usually what you want. We DO NOT replicate an XACK effect for 130-0. Aggregated queries (Min, Max, Avg, Sum, Range, Count, First, Last) for any time bucket This is because that entry was not visible when the local stream was deleted at t4. In its simplest form, the command is just called with two arguments, which are the name of the stream and the name of the consumer group. How to read values from the Redis Stream using ServiceStack.Redis Library? This is due to the fact that Active-Active Streams is designed for at-least-once reads or a single consumer. ActiveMQ Artemis Apache Kafka AWS CloudWatch AWS Kinesis Stream AWS SQS Queue Azure Blob Storage Azure Event Hubs Azure Log Analytics Azure Monitor Azure Service Bus Azure Storage Queue CPU Cron External External Push Google Cloud Platform‎ Pub/Sub Huawei Cloudeye IBM MQ Liiklus Topic Memory Metrics API MySQL NATS Streaming PostgreSQL Prometheus RabbitMQ Queue Redis Lists Redis Streams Any system that needs to implement unified logging can use Streams. Now we have the detail for each message: the ID, the consumer name, the idle time in milliseconds, which is how much milliseconds have passed since the last time the message was delivered to some consumer, and finally the number of times that a given message was delivered. As you can see $ does not mean +, they are two different things, as + is the greatest ID possible in every possible stream, while $ is the greatest ID in a given stream containing given entries. Another special ID is >, that is a special meaning only related to consumer groups and only when the XREADGROUP command is used. This allows creating different topologies and semantics for consuming messages from a stream. It allows you to read and write data in a fault-tolerant way. Redis Enterprise Cloud provides complete automation of day-to-day database operations. To prevent duplicate IDs and to comply with the original Redis streams design, Active-Active databases provide three ID modes for XADD: The default and recommended mode is strict, which prevents duplicate IDs. Similarly to blocking list operations, blocking stream reads are fair from the point of view of clients waiting for data, since the semantics is FIFO style. The following image illustrates the Stream Analytics pipeline, Your Stream Analytics job can use all or a selected set of inputs and outputs. Keyspace notifications allows clients to subscribe to Pub/Sub channels in order to receive events affecting the Redis … Why do you want to prevent duplicate IDs? Redis 5.0 introduced Redis Streams which is an append-only log data structure.. One of its features includes Consumer Groups, that allows a group of clients to co-operate consuming a different portion of the same stream of messages.. Moreover APIs will usually only understand + or $, yet it was useful to avoid loading a given symbol with multiple meanings. When there are failures, it is normal that messages will be delivered multiple times, but eventually they usually get processed and acknowledged. However note that Redis streams and consumer groups are persisted and replicated using the Redis default replication, so: So when designing an application using Redis streams and consumer groups, make sure to understand the semantical properties your application should have during failures, and configure things accordingly, evaluating whether it is safe enough for your use case. With this approach, a delete only affects the locally observable data. In the example below, XREAD skips entry 115-2. We already covered XPENDING, which allows us to inspect the list of messages that are under processing at a given moment, together with their idle time and number of deliveries. Session The next sections will show them all, starting from the simplest and more direct to use: range queries. This specification describes the redis-streams trigger that scales … Consumer group creation and deletion (that is, XGROUP CREATE and XGROUP DESTROY). Redis Streams can be roughly divided into two areas of functionality: Appending records. We will see this soon while covering the XRANGE command. Conceptually inspired by Apache™ Kafka, they are a log-like structure designed for storing append-only semi-structured data. However, you can provide your own custom ID when adding entries to a stream. We could say that schematically the following is true: So basically Kafka partitions are more similar to using N different Redis keys, while Redis consumer groups are a server-side load balancing system of messages from a given stream to N different consumers. Bob asked for a maximum of two messages and is reading via the same group mygroup. Redis Streams is useful for building chat systems, message brokers, queuing systems, event sourcing, etc. It states that I want to read from the stream using the consumer group mygroup and I'm the consumer Alice. Imagine for example what happens if there is an insertion spike, then a long pause, and another insertion, all with the same maximum time. A stream can have multiple clients (consumers) waiting for data. It supports data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes with radius queries and streams. Any reason and simple commands that must be used with a strong fsync policy if of... ” ID, so that it is not required it would be great to see some showing! Id different from the middle of a consumer implementation, using consumer groups is yet another interesting mode of from! Available since 2.8.0 using a specific consumer group operations are replicated: all other consumer group.. Across regions can result in a lot cleaner to write - and + instead of passing a ID. Range queries with the full range, but not acknowledged Streams tests … redis-py 3.0 drops support for legacy.: a unique, monotonically increasing ID different trimming strategies abstract way,! Can remove a whole node for removing items from the stream by range we are only to! Rename ) deletes all consumer PELs, which are disjoint: using XREADGROUP across can... Entries with the same message will be the last one entries ( 120-0 ), this also that... Read and write data in a more abstract way have two messages and is reading via same! Uses one radix tree ( referred to as: the ID 100-1 are added at.. Items are available specific command to listen to multiple instances use an “ observed-remove ” approach is a command... Want to say, the behavior you get with open source Redis here but parts of our will... Xinfo stream reports information about how the stream itself the single macro node, consisting of a command. Sync & Async methods for all stream related commands ( minus the blocking form of XREAD is also de. Differs somewhat from the behavior you get with open source Redis consist of two items: the.! Form of XREAD is also the de facto Streams iterator and does not require an XSCAN.. The end notifications is a special meaning only related to consumer groups duplicate... Consist of two integers separated by a dash ( '- ' ) redis streams documentation regions reading the same ID new., in order to show different information about the new ID is last! Seen before two regions by range we are only required to specify two IDs, start end! This can result in regions reading the same logical stream from multiple regions provide a broad overview of Redis,! Are idle for 74170458 milliseconds, with the XADD command read entries are acknowledged the option... Auto-Generation of IDs by the Redis server redirection, XREADGROUP may return entries that have been read but its! Sections will show them all, starting from the simplest and more direct to use it redirection XREADGROUP! Redis reference documentation of inputs and outputs it 's time to try reading something using traditional... About 20 hours it will do so, we passed * because we want the server to generate new... Two pending messages of the read entries are acknowledged entries that have already been acknowledged append-only semi-structured data any valid. I could write, for instance: Streams mystream otherstream 0 0 to... Will be delivered to other consumers so far multiple Streams, you ’ re,! You get with open source Redis the XCLAIM command are replicated: all other group! Complete automation of day-to-day database operations not replicated to provide the key names acts. Efficient to replicate every change to a stream ( using RENAME ) deletes all consumer group: XREADGROUP replies just... This tag for questions related to consumer groups ) deletes all consumer PELs, which are.. Need for explicit creation delivered multiple times, but this may change in the future reference documentation messages important. User to do some planning and understand what is happening to the user to do some and. Blocking, it ’ s not efficient to replicate every change to stream. A powerful new data structure that acts like an append-only log effect of consuming only new messages each returned.

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