SingleStore
Relational databases
Real-time analytic database software
Vector database software
Database software
- Features
- Ease of use
- Ease of management
- Quality of support
- Affordability
- Market presence
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What is SingleStore
SingleStore is a distributed SQL database designed to support real-time analytics and operational workloads on the same platform. It targets teams building data-intensive applications that need fast ingest, low-latency queries, and SQL-based access for BI and application services. The product combines rowstore and columnstore storage, supports scale-out clustering, and offers deployment options in managed cloud and self-managed environments. It also provides vector search capabilities for similarity queries alongside relational data.
Unified HTAP-style workloads
SingleStore supports both transactional-style operations and analytical queries within one distributed SQL system. Its rowstore and columnstore options allow different access patterns without moving data into a separate analytics engine. This can reduce data duplication and pipeline complexity for near-real-time dashboards and application analytics. It is suited to use cases where freshness and query latency matter more than strict separation of OLTP and OLAP systems.
Scale-out distributed architecture
The platform is designed to scale horizontally across nodes, which helps when data volume and concurrency exceed a single server’s limits. It provides clustering and distributed query execution to spread ingest and query workloads. This architecture aligns with large, continuously growing datasets and multi-tenant application patterns. It offers an alternative to single-instance deployments that require vertical scaling.
SQL plus vector search
SingleStore provides SQL interfaces and integrates vector data types and similarity search to support AI-enabled retrieval patterns. This enables teams to keep structured data and embedding-based search in one database layer for certain applications. It can simplify application architecture compared with running separate systems for relational queries and vector retrieval. The approach is useful when vector search needs to join with relational filters and aggregations.
Operational complexity at scale
Running a distributed database introduces cluster-level concerns such as node sizing, data distribution, and failure handling. Even with managed offerings, teams often need to understand partitioning, workload isolation, and query tuning to achieve predictable performance. This can be more complex than operating a single-node relational database service. Organizations without distributed-systems experience may face a steeper learning curve.
Not a full OLTP replacement
While it supports transactional patterns, some workloads that require extensive relational features, strict transactional semantics across many tables, or deep ecosystem compatibility may fit better in traditional OLTP-focused databases. Application portability can be affected by differences in SQL dialect, indexing behavior, and operational tooling. Teams may need to validate feature parity for existing applications before migrating. This is especially relevant for legacy systems tightly coupled to a specific database engine.
Vector feature maturity varies
Vector search capabilities in general-purpose databases can lag specialized vector engines in areas like advanced indexing options, recall/latency tuning controls, and rapidly evolving retrieval features. Performance and functionality depend on dataset size, embedding dimensionality, and query patterns. Teams building retrieval-heavy applications may need benchmarking to confirm fit. Some architectures may still require a dedicated vector store for specific requirements.
Plan & Pricing
Pricing model: Pay-as-you-go (managed Helios Cloud with usage-based Compute credits + Storage + Data transfer)
Free tier/trial:
- Free Shared Tier: 1 Free Workspace (permanently free shared workspace for evaluation/development).
- Free trial/credits: Standard plan notes "Start with $600 in free credits" (site offers free credits for evaluation).
Compute (examples from official Helios pricing table, AWS US East 1 sample):
- S-00 — 2 vCPU / 16 GB — 0.25 CR / hour — $0.99 per hour
- S-0 — 4 vCPU / 32 GB — 0.5 CR / hour — $1.98 per hour
- S-1 — 8 vCPU / 64 GB — 1 CR / hour — $3.96 per hour
- S-2 — 16 vCPU / 128 GB — 2 CR / hour — $7.92 per hour
- S-4 — 32 vCPU / 256 GB — 4 CR / hour — $15.84 per hour
- (Full size table available on vendor pricing page.)
- Compute credit list price: $3.96 per Credit (on-demand).
Editions / Plan labels (Helios Cloud):
- Shared (Free) — 1 Free Workspace; intended for evaluation/development/non-production.
- Standard (Managed) — "Starts at $0.99/hr" for on-demand sizes; includes read-replicas, DB branching, 30-day monitoring, standard support. (Also a BYOC Standard option — contact for pricing.)
- Enterprise (Managed) — "Starts at $1.49/hr"; enhanced DR & security features; contact sales for full pricing.
Storage (examples):
- Price per average GB/month by tier: Tier 1 $0.023/GB-mo; Tier 2 $0.025/GB-mo; Tier 3 $0.026/GB-mo; Tier 4 $0.040/GB-mo; BYOC: CSP billed.
Data transfer / Flow:
- Flow processing price: $0.02 per GB processed (preview wording).
- Data egress pricing: per-TB rates vary by source/destination region (examples listed on vendor page; e.g., US East 1 -> other same CSP regions $20 per TB; Internet/different CSP ~$90 per TB — see vendor page for full table).
Notes / discounts / commitments:
- On-demand billing at list price; monthly billing based on actual usage. Vendor mentions commitment/volume discounts and contact sales for commitments and BYOC pricing.
(Formatted from official SingleStore Helios / Pricing pages.)
Seller details
SingleStore, Inc.
San Francisco, CA, USA
2011
Private
https://www.singlestore.com/
https://x.com/singlestoredb
https://www.linkedin.com/company/singlestore/
