Utilizing the Amazon MSK Native Connector to Rockset


Rockset’s native connector for Amazon Managed Streaming for Apache Kafka (MSK) makes it less complicated and sooner to ingest streaming knowledge for real-time analytics. Amazon MSK is a completely managed AWS service that provides customers the power to construct and run purposes utilizing Apache Kafka. Amazon MSK supplies control-plane operations resembling creating and deleting clusters, whereas permitting customers to make use of Apache Kafka data-plane operations for producing and consuming knowledge.

With the MSK integration, customers don’t must construct, deploy or function any infrastructure parts on the Kafka facet. Right here’s how Rockset is making it simpler to ingest streaming knowledge from MSK with this knowledge integration:

  • The combination is managed fully by Rockset and might be arrange with only a few clicks, conserving with our philosophy of creating real-time analytics accessible.
  • The combination is steady so any new knowledge within the Kafka matter will get listed in Rockset, delivering an end-to-end knowledge latency of round two seconds.
  • There isn’t a must pre-create a schema to run real-time analytics on occasion streams from Kafka. Rockset indexes all the knowledge stream so when new fields are added, they’re instantly uncovered and made queryable utilizing SQL.

Underneath the Hood

Rockset’s Kafka integration adopts the Kafka Shopper API, which is a low-level, vanilla Java library that may be simply embedded into purposes to tail knowledge from a Kafka matter.

While you create a brand new assortment from an Amazon MSK integration and specify a number of subjects, Rockset tails these subjects utilizing the Kafka Shopper API and consumes knowledge in actual time. Rockset handles all of the heavy lifting resembling progress checkpointing and addressing frequent failure circumstances with the Aggregator Leaf Tailer Structure (ALT). The consumption offsets are utterly managed by Rockset, with out saving any info inside a buyer’s cluster. Every ingestion employee receives its personal matter partition project and final processed offsets throughout the initialization from the ingestion coordinator, after which leverages the embedded client to fetch Kafka matter knowledge.

The primary distinction between Amazon MSK and Confluent Kafka in Rockset’s Kafka integration is how we authenticate along with your cluster. Amazon MSK makes use of IAM for safe authentication, so we added assist for IAM authentication utilizing AWS Cross-Account IAM Roles. While you create a brand new Amazon MSK integration and supply a Cross-Account IAM function, Rockset authenticates along with your MSK cluster utilizing the Amazon MSK Library for IAM.

Amazon MSK and Rockset for Actual-Time Analytics

As quickly as occasion knowledge lands in MSK, Rockset routinely indexes it for sub-second SQL queries. You may search, mixture and be part of knowledge throughout Kafka subjects and different knowledge sources together with knowledge in S3, MongoDB, DynamoDB, Postgres, and extra. Then, merely flip the SQL question into an API to serve knowledge in your software.

We’ve additionally load examined the brand new MSK integration with pattern knowledge and numerous load configurations, sending a max throughput of roughly 33 MB/s.


Fast Amazon MSK Setup

Arrange the Integration

To arrange an Amazon MSK Integration, first go to the integrations web page on the Rockset console. Choose the Amazon MSK choice and click on “Begin” to start creating your MSK integration and supply info for Rockset to connect with your cluster.


Present a reputation on your integration together with an elective description. Create a brand new IAM coverage and fix the coverage to a brand new or current IAM function to present Rockset learn entry to your MSK cluster. Present the function ARN for the IAM function and the bootstrap servers URL out of your MSK cluster’s dashboard.



Create a Assortment

A set in Rockset is just like a desk within the SQL world. To create a group, merely add in particulars together with the Kafka matter(s) you need Rockset to eat. The beginning offset lets you backfill historic knowledge in addition to seize the most recent streams.


Question Subject Information utilizing SQL

As quickly as the info is ingested, Rockset will index the info in a Converged Index for quick analytics at scale. This implies you possibly can question semi-structured, deeply nested knowledge utilizing SQL with no need to do any knowledge preparation or efficiency tuning.

On this instance, we are able to merely write a SQL question on the Amazon MSK knowledge we have simply arrange the combination for, going from setup to question in a matter of minutes.


We’re excited to proceed to make it simple for builders and knowledge groups to research streaming knowledge in actual time. If you happen to’re a person of Amazon MSK, it’s simpler now than ever earlier than with Rockset’s native assist for MSK.


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