DolphinDB
The world's fastest distributed time-series database
The world's fastest distributed time-series database
Published Sep 29, 2026
Vendor news suggests ongoing expansion into multi-model capabilities (e.g., vector/text) and heterogeneous computing (GPU). Concrete, dated roadmap artifacts were not identified in this research pass.
Vendor and partner materials reference TB–PB scale handling; however, no independent benchmark suite or reproducible evidence was identified in this research pass.
As noted above, certifications and a consolidated enterprise security feature checklist are not clearly published in the reviewed materials; buyers should treat this as a procurement risk until clarified.
1) Unified batch and streaming computation within a single platform
A third-party blog comparing DolphinDB and TimescaleDB reports notable performance advantages for DolphinDB in import, space usage, and query performance. However, this is not a standardized benchmark suite with broad peer review; methodology, hardware configurations, tuning parameters, and dataset representativeness should be scrutinized. Such results should be treated as directional and validated in a POC.
Best fit appears to be mid-market to enterprise organizations with dedicated data engineering, quantitative, or platform teams.
Decision makers:
End users:
Primary beachhead appears to be quantitative finance (market data centers, factor research, strategy backtesting, risk control, trading infrastructure), with expansion into IoT/industrial time-series and other verticals that handle high-frequency metrics.
Get a comprehensive analysis of DolphinDB including market position, competitive landscape, adoption trends, and peer benchmarks.
Download full report →If the primary requirement is Postgres-compatible time-series with a managed cloud offering and published compliance documentation. Timescale often aligns better with these requirements due to Postgres compatibility, published pricing, and clearer enterprise security/compliance packaging.
If the organization prioritizes a very large open-source community and a broad hiring pool. ClickHouse, Timescale, and Influx ecosystems may provide easier staffing and integration.
If the organization seeks to avoid dependence on a proprietary scripting/compute model. DolphinDB is commercial and uses its own language and engines; migrating away may require significant effort.
If the organization lacks platform engineering capacity (especially for Kubernetes). Even with marketplace offerings, operating a high-performance distributed database requires operational capability; if the product is not operated effectively, expected performance benefits may not be realized.
If procurement requires abundant third-party peer reviews as a gating criterion. DolphinDB’s limited presence on G2/Capterra/TrustRadius in this research pass could present a challenge for some procurement processes.
Validated primarily by official documentation and partner materials (not by large-scale independent reviews):
Balanced note: these differentiators are presented in vendor materials and partner announcements and should be validated through a POC and reference checks.
A limitation of this research pass is limited coverage on mainstream B2B review platforms:
Interpretation: DolphinDB may have limited presence on mainstream Western review platforms or may be listed under different naming/packaging. This reduces the ability to benchmark customer sentiment via standardized third-party review data.
Because verified review quotes were not found, the following are not customer reviews but indicate positioning and some external mentions:
Balanced takeaway: the evidence base for independent customer sentiment from mainstream review platforms is limited in public channels. Procurement should include direct reference calls and a proof-of-concept (POC).
Critical evaluation:
Critical evaluation:
Critical evaluation:
DolphinDB is a commercial, distributed time-series database and real-time analytics platform designed to unify storage, compute, and streaming for high-throughput ingestion, low-latency querying, and in-database analytics. The vendor describes it as a real-time platform for analytics and stream processing with multiple storage engines (time-series, OLAP, in-memory OLTP, etc.) and a built-in scripting/programming language with a large function library.
Vendor materials highlight:
Sources: product page and documentation describe multi-engine storage, distributed architecture, and streaming framework.