SingleStore Kai
SingleStore Kai is an API compatibility layer that turbocharges MongoDB analytics by up to 100x without requiring any changes to existing queries or application code.
Publisher review
SingleStore Kai is an API compatibility layer that turbocharges MongoDB analytics by up to 100x without requiring any changes to existing queries or application code. It is designed for organizations that need real-time analytics on JSON data while preserving their MongoDB investment. The platform is built for fast data ingest, high concurrency, and low-latency queries, making it suitable for in-product analytics, operational dashboards, and AI-powered applications. It supports multiple data models including SQL, vector search, full text, time series, and geospatial data, and is available in the cloud, on Kubernetes, or on-premises.
SingleStore Kai works by acting as a drop-in replacement for the MongoDB query protocol, translating MongoDB wire protocol requests into SingleStore's distributed SQL engine. It provides vector and semantic searches on JSON data using index types such as FLAT, IVF_FLAT, IVF_PQ, HNSW_FLAT, and HNSW_PQ, with similarity matching via dot product and Euclidean distance. The system also includes a Change Data Capture (CDC) solution for streaming data from MongoDB into SingleStore Kai, enabling real-time synchronization. SingleStore is used by top brands such as NVIDIA, Goldman Sachs, LG, Adobe, Siemens, Hulu, Cigna, STC, Dell Technologies, Samsung, Kroger, and Comcast.
In the market, SingleStore Kai competes directly with MongoDB, Oracle Database, Google Cloud Platform, and MemSQL. Unlike MongoDB, which requires dedicated search nodes to separate search from CRUD performance, SingleStore Kai integrates vector search directly into its distributed SQL engine, eliminating the need for separate infrastructure. However, SingleStore is not a MongoDB partner, and its vector indices can only be created on columnstore tables, which may limit flexibility for some workloads. The platform has received an overall rating of 4.5 stars from nearly two dozen reviews on Gartner Peer Insights.
Key trade-offs include higher-tier plans that can be expensive, a learning curve for advanced features like vector indexing and CDC configuration, and variable customer support response times. The mobile app has limited functionality, and some features require deep technical knowledge to implement effectively. While SingleStore Kai offers up to 100x performance gains for MongoDB analytics, organizations must weigh these benefits against the cost and complexity of migrating or integrating with their existing data stack.
How it works
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100x MongoDB analytics acceleration
Turbocharges MongoDB analytics by up to 100x without changing queries or application code, using SingleStore's distributed SQL engine.
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Dual SQL and NoSQL support
Supports both SQL and NoSQL data models, allowing developers to query JSON data with familiar MongoDB syntax or standard SQL.
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Vector and semantic search
Offers vector and semantic searches on JSON data using index types like HNSW_FLAT and IVF_PQ, with dot product and Euclidean distance.
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Real-time data ingestion
Provides a Change Data Capture (CDC) solution for streaming data from MongoDB to SingleStore Kai, enabling real-time synchronization.
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Multi-model data support
Supports SQL, vector search, full text, time series, and geospatial data models within a single distributed database.
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High concurrency and low latency
Built for fast ingest, high concurrency, and low-latency queries, handling billions of vectors with interactive response times.
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Flexible deployment options
Available in the cloud, on Kubernetes, or on-premises, giving organizations control over data residency and infrastructure.
Strengths and trade-offs
Strengths
- Delivers up to 100x faster analytics on JSON data compared to native MongoDB, without requiring query or code changes.
- Integrates vector search directly into the SQL engine, eliminating the need for separate vector databases or dedicated search nodes.
- Supports multiple data models (SQL, NoSQL, vector, full text, time series, geospatial) in a single distributed system.
- Used by major enterprises including NVIDIA, Goldman Sachs, Adobe, Siemens, Hulu, and Samsung, with a 4.5-star Gartner Peer Insights rating.
Trade-offs
- Higher-tier plans can be expensive, potentially exceeding budgets for smaller teams or startups.
- Advanced features like vector indexing and CDC configuration require significant technical expertise to implement correctly.
- Customer support response times vary, with some users reporting delays during critical incidents.
- Vector indices can only be created on columnstore tables, limiting indexing flexibility for certain workload types.
Pricing context
Contact for pricing; no public tier or dollar figures available. A free trial is offered.
Getting started with SingleStore Kai
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Sign up for SingleStore Kai
Go to the SingleStore website and sign up for a free trial. Provide your email and organization details. After verification, you will receive access to the SingleStore Kai cloud environment or a download link for on-premises deployment.
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Connect your MongoDB data
Configure the Change Data Capture (CDC) connector to stream data from your MongoDB instance into SingleStore Kai. Set up the connection parameters including host, port, and authentication credentials to enable real-time synchronization.
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Create a columnstore table
In the SingleStore Kai interface, create a columnstore table to store your JSON data. Define the schema or use automatic schema detection. Note that vector indices can only be created on columnstore tables, so this step is essential for advanced queries.
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Run a MongoDB query
Use your existing MongoDB client or application to send a query to SingleStore Kai. Because Kai acts as a drop-in replacement for the MongoDB wire protocol, your query executes without modification, leveraging SingleStore's distributed SQL engine for faster analytics.
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Schedule data synchronization
Set up a recurring schedule for the CDC pipeline to keep your SingleStore Kai data in sync with MongoDB. Configure the sync interval based on your latency requirements, ensuring real-time or near-real-time updates for operational dashboards and analytics.
Frequently Asked Questions
What is SingleStore Kai and how does it work?
SingleStore Kai is an API compatibility layer that accelerates MongoDB analytics up to 100x by translating MongoDB wire protocol requests into SingleStore's distributed SQL engine. It requires no changes to existing queries or application code, acting as a drop-in replacement.
How does SingleStore Kai compare to MongoDB for analytics?
SingleStore Kai offers up to 100x faster analytics on JSON data compared to native MongoDB. Unlike MongoDB, which needs dedicated search nodes, SingleStore Kai integrates vector search directly into its SQL engine, eliminating separate infrastructure and simplifying deployment.
What vector search index types does SingleStore Kai support?
SingleStore Kai supports FLAT, IVF_FLAT, IVF_PQ, HNSW_FLAT, and HNSW_PQ index types for vector and semantic searches on JSON data. It uses similarity matching via dot product and Euclidean distance, enabling efficient vector queries.
How much does SingleStore Kai cost?
SingleStore Kai requires contacting for pricing, as no public tier or dollar figures are available. A free trial is offered. Higher-tier plans can be expensive, potentially exceeding budgets for smaller teams or startups.
What are the deployment options for SingleStore Kai?
SingleStore Kai is available in the cloud, on Kubernetes, or on-premises. This flexibility gives organizations control over data residency and infrastructure, allowing them to choose the deployment that best fits their operational needs.
What are the limitations of SingleStore Kai?
Vector indices can only be created on columnstore tables, limiting indexing flexibility. Advanced features like vector indexing and CDC configuration require significant technical expertise. Customer support response times vary, and higher-tier plans can be expensive.
Alternatives
How SingleStore Kai compares
Direct head-to-head against 3 competitors. Picked by 7wData.
SingleStore Kai
- Pricing
- Contact for pricing; no public tier or dollar figures available. A free trial is offered.
- Target
- SingleStore Kai is an API compatibility layer that turbocharges MongoDB analytics by up to 100x without requiring any changes to existing queries or application code.
- Strength
- Delivers up to 100x faster analytics on JSON data compared to native MongoDB, without requiring query or code changes.
- Watch for
- Higher-tier plans can be expensive, potentially exceeding budgets for smaller teams or startups.
MongoDB
- Pricing
- $57/month for shared, $0.08/hour for dedicated
- Target
- Document-oriented workloads with flexible schema
- Deployment
- Cloud/On-prem
- Strength
- Native JSON handling and horizontal scaling
- Watch for
- Analytical query performance limitations
Amazon Aurora
- Pricing
- $0.10/hour for serverless, $0.28/hour for provisioned
- Target
- MySQL/PostgreSQL-compatible OLTP workloads
- Deployment
- AWS Cloud
- Strength
- High availability with multi-AZ replication
- Watch for
- Cost escalations with storage scaling
ClickHouse
- Pricing
- Open-source free, $1.25/hour for cloud
- Target
- Analytical queries on large datasets
- Deployment
- Self-managed/Cloud
- Strength
- Columnar storage for fast aggregations
- Watch for
- Transactional workload limitations
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Sources
Reporting on this tool draws on these publicly available sources.