SQL on DynamoDB

SQL Search and Analytics for Amazon DynamoDB

Real-time APIs and dashboards on DynamoDB

Powerful Analytics on DynamoDB Without Any ETL

Rockset is a fully managed service that enables real-time search and analytics on raw data from Amazon DynamoDB – with full featured SQL. Rockset takes an entirely new approach to loading, analyzing and serving data so that you can run powerful SQL analytics on data from DynamoDB without ETL.

Use Cases

Real-time dashboards

To make live dashboards possible, Rockset reflects new data in seconds and delivers query responses in milliseconds. To bring interactive dashboards and drilldowns to life, Rockset supports high concurrency and thousands of queries per second.

Data as an API

APIs are a critical part of the strategy for fast-moving developers building on a global scale. Rockset uses an API-first approach so you can deliver your data as an API and allow your developers to build applications faster.

Recommendation engines

Combine real-time behavioral data with historical data. Infer user preferences in real time. Personalize user experiences by recommending the right actions at the right time by using Rockset's real-time sort, filter and search functionality.

Operational Analytics on Data from DynamoDB

As an operational data store optimized for transactions, DynamoDB is not well suited for analytics. Use Rockset to run powerful ad hoc analytical queries that are not possible on DynamoDB. New data is queryable in seconds and queries return in milliseconds, so performance is no longer a limiting factor.

Continuously load data from DynamoDB

Rockset delivers low data latency through native integration with DynamoDB. Rockset initially batch loads data from DynamoDB, then switches to continuous tailing to stay in sync, with no more than few seconds delay. It automatically monitors to ensure consistency between DynamoDB and Rockset and purges old data using time-based retention policies. No ETL tools like AWS Glue required.

Explore unstructured data as SQL tables

Rockset enables millisecond SQL including joins, filters, aggregates and full text search. It schemalessly ingests raw data, including nested JSON, and represents them as SQL tables that automatically adapt to any data changes in DynamoDB. Join, filter, aggregate across datasets without upfront schema definitions.

Deliver real-time APIs & dashboards

Rockset delivers low query latency with cloud-native auto-scaling and performance isolation. Real-time applications can programmatically access Rockset via Python, Java, Javascript, GO or REST APIs and live dashboards can use SQL clients like Tableau, Redash, Apache Superset or others via the JDBC connector. Deploy operational analytics in production without staging in temporary databases.

How It Works

Rockset continuously tails DynamoDB so you don't have to manage ETL pipelines. It uses converged indexing to deliver real-time SQL over REST with serverless auto-scaling under the hood.

Visualization Tools

Enable your business teams to visualize real-time event streams using dashboarding tools that they already know and love, using Rockset's JDBC connector and native support for standard SQL-based visualization tools.

Grafana

Grafana is an open observability platform for analytics and monitoring. Grafana requires a SQL backend and cannot query Kafka directly. Use Rockset to visualize Kafka events in Grafana.

Learn more

API Access

Insert, update and query data programmatically from custom application code using Rockset's client libraries wrapped on top of REST.

Python

# connect to Rockset
from rockset import Client, Q, F
rs = Client()

# build a query object
q = Q('hello_world').where(F['name'] == 'Jim Gray')
results = rs.sql(q)

Rockset’s Python package is called rockset and the entire API is contained within a single Python module called rockset. APIs defined in the rockset module allow you to securely connect to the Rockset service, create or manage collections and query Rockset.

Learn more

# connect to Rockset
from rockset import Client, Q, F
rs = Client()

# build a query object
q = Q('hello_world').where(F['name'] == 'Jim Gray')
results = rs.sql(q)

Powerful Analytics on DynamoDB Without Any ETL

Resources

Related Blog

Comparing options for analytics on DynamoDB

A comparison of real-time analytics options on DynamoDB - Athena, Spark and Elastic - in terms of ease of setup, maintenance and query capability.

Related Blog

Custom live dashboards on DynamoDB

Live dashboards are used to support mission- critical decisions on real-time data. We cover different approaches to live dashboards on DynamoDB.

Related Blog

Standard BI dashboards on DynamoDB

We review several approaches to building operational dashboards and reporting, using standard BI tools like Tableau, on DynamoDB data.

How-To Guide

Using Tableau with DynamoDB

We will demonstrate how you can build an interactive dashboard with Tableau, using SQL on data from DynamoDB, in a series of easy steps, with no ETL involved.

How-To Guide

Running Fast SQL on DynamoDB Tables

Have you ever wanted to run SQL queries on Amazon DynamoDB tables without impacting your production workloads? Learn how in this guide.

Documentation

How to use DynamoDB tables as data source

Read up on how to securely connect DynamoDB tables in your AWS account with Rockset and create collections which sync your data in real time.

Our Customers

See how the most innovative companies do more with their data, faster.

"Building our dashboard on Rockset was the easiest way to analyze our call data in DynamoDB and get real-time insights on the metrics we care about."

-Naresh Talluri, product manager at FULL Creative

Grafana

Python

Comparing options for analytics on DynamoDB

Custom live dashboards on DynamoDB

Standard BI dashboards on DynamoDB

Using Tableau with DynamoDB

Running Fast SQL on DynamoDB Tables

How to use DynamoDB tables as data source

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