Migrate from Rockset to SingleStore


Rockset is a real-time analytics database that was recently acquired by OpenAI. As a result of this acquisition, all existing customers will be transitioned off of Rockset and will need to find an alternative solution as detailed in the Rockset FAQ.

Rockset is popular due to its ability to store schemaless JSON data, offer fast ingestion, run real-time analytics on immense volumes of data, handle upserts, and support complex queries like JOINS. SingleStore checks all of these boxes while providing  an even greater ability to build intelligent applications with powerful vector and search capabilities, and manage enterprise data with key security and manageability features.

SingleStore is a great alternative for your application needs and this guide will help you through the migration process.


Please fill out this form to have SingleStore assist you with your Rockset migration.

Rockset Key Concepts and How They Map to SingleStore

Ingestion for Data Sources

Rockset supports ingestion from a variety of data sources including streaming services, databases, and object stores. SingleStore supports most of the sources supported by Rockset along with additional sources. SingleStore provides native high-speed ingestion with pipelines, which support one-time loads up to massively-parallel incremental updates.

Data Source



Apache Kafka



Amazon S3

Amazon MSK

Google Cloud Storage

Azure Blob storage

Confluent Cloud


Iceberg + Catalog

Partner integration solutions for:

  • Azure Event Hubs

  • Microsoft SQL Server

  • Oracle

  • PostgreSQL

Ingest Transformation

Rockset transforms data during ingestion. SingleStore supports data transformation through SQL-based procedures, which can effectively achieve the same behavior. These transformations are applied to both the initial data load and to new data that is ingested into SingleStore.


A set of Rockset documents is a collection, which is similar to tables in a relational database like SingleStore. Rockset allows querying this data either via SQL or through Query Lambdas. Similarly, SingleStore allows the data stored in relational tables to be queried via SQL, SingleStore Kai (for MongoDB® data sources), or a Data API that allows HTTP API access to SingleStore databases.


Aliases are used to associate multiple names with Rockset collections, which is a concept that  SingleStore does not support.


Views are virtual collections defined by SQL queries. A view’s SQL query may reference nothing, or may reference other views, collections, or aliases. SingleStore also supports views.


Workspaces are containers that hold Rockset resources such as collections, Query Lambdas, views, aliases,  and even other workspaces. SingleStore has a highly advanced version of workspaces that are elastic, with support for auto-scaling, and that provide complete role-based access control (RBAC), security, and isolation. Workspaces in SingleStore can be created from either a UI or via the Management API.

Refer to Rockset vs. SingleStore for a comprehensive technical comparison between these two platforms.

Key Workload Considerations

Some of the key features for Rockset can be mapped to similar features in SingleStore which may also have additional capabilities.

Rockset supports text search as part of its product offering, and provides full-text search via the SEARCH function. SingleStore not only matches these features but provides much richer search functionality with support for Java-based Lucene full-text search with the recent release of SingleStore v8.7.

Rockset added support for vector search using a similarity index, which is used for indexing the embeddings. However, there is no choice of indexing algorithm, which is an IVF_PQ index with support for dot, cosine, and Euclidean distance metrics.

SingleStore supports vector indexing with advanced algorithms like HSNW and IVF_PQ, and you can combine indexed vector search with full-text indexing. You can also combine vector search with queries over other data types, including JSON, time-series, full-text, spatial, and key-value data. SingleStore includes both exact K Nearest Neighbor (KNN) and indexed Approximate Nearest Neighbor (ANN). Provided distance metrics include dot product and Euclidean distance.

JSON Data Support

JSON-based storage and query execution capabilities and compatibility with MySQL queries make it easy to migrate and translate Rockset queries over to SingleStore.

SingleStore provides a rich set of capabilities in JSON data processing for analytics and excels at delivering analytics on immense volumes of data, as evidenced by the performance of SingleStore Kai.

SingleStore supports seekable columnstore (universal storage) and columngroup indexes to allow combined row and columnar access to large tables. Indexes can be added to increase query performance and text indexes added on the JSON column to match for query strings over any field on JSON data.

SingleStore supports MySQL-style queries on JSON data which helps ease the migration of Rockset queries into SingleStore, thereby allowing further access to the MySQL ecosystem and MySQL-based tooling.


Rockset is not a transactional database and is not designed to support OLTP workloads. Rockset provides atomic writes at the document level. While multiple fields can be updated atomically within a single document, atomic updates to more than one document are not supported. All writes are asynchronous, where the period from when data is written to the database to when the data is visible to queries varies between 1 and 5 seconds, which affects real-time responsiveness.

Conversely, SingleStore is an ACID-compliant database with support for transactions. Consolidating the entire data stack while providing  analytics on the same data storage is achievable.

Security and Enterprise Readiness

When considering where to run production workloads, it is critical to select a platform that is both secure and that can run these workloads at scale.




Continuous backups with data stored on SSDs for performance, and cloud storage for durability with disaster recovery

Multi-region hot-cold and hot-hot deployment options

Enterprise SLAs

Security Compliance

  • SOC 2 Type II


  • GDPR

  • CCPA

Data security and networking

  • Single Sign-On with Okta and custom SSO

  • Data encrypted at rest and in transit

  • Role-Based Access Control (RBAC)

  • IP Allowlisting

  • AWS PrivateLink

  • Virtual Private Rockset in your VPC

Performance metric endpoint

Last modified: July 3, 2024

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