Virtuoso suits teams integrating relational, graph, XML, and web data across hybrid or self-hosted deployments.
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Best Multimodel Databases 2026
When an application relies on different kinds of data, compare which models a database supports and how you can query them. These entries are ordered as a ranked best-of list, with Amazon DynamoDB, ArcadeDB, and CrateDB among those near the top. Look at graph querying, SQL support, and vector search alongside supported data models to see which capabilities match your work. Deployment options and multi-region support offer further points to weigh for your intended environment. Free-plan availability and paid-from pricing can help you compare costs. Use the listed criteria to narrow down which database capabilities and operating options matter most for your applications.
ArcadeDB
ArcadeDB may suit developers building knowledge graphs, GraphRAG, fraud detection, recommendation engines, real-time analytics, customer 360, supply-chain analytics, or…
WebWindowsMac+3CrateDB
CrateDB may suit teams analyzing live operational data across varied data types, including time-series, JSON, and geospatial data.
WebWindowsMac+3SingleStore Helios
Helios suits teams that need a cloud database for transactional and analytical work, with multiple data models or AI workloads.
WebWindowsMac+3Amazon DynamoDB
DynamoDB suits teams building cloud applications that need managed NoSQL storage, automatic scaling, or multi-Region operation.
AndroidiPhone & iPadWeb+5Aerospike Database suits teams building transaction systems or data pipelines that need key-value, document or graph data models.
DolphinDB suits teams that need real-time analytics or stream processing, including those working in finance, energy, transportation, manufacturing, or scientific…
InterSystems IRIS is positioned for teams building data-intensive, mission-critical applications that need database, integration, and analytics capabilities.
It suits teams building document-database workflows that need search, integrations, deployment choices, or AI features.
It suits teams building high-velocity data applications that need distributed SQL, transactions, or streaming writes.
It suits developers building on-premises applications that need multiple data models and deployment options.
Spanner suits application teams needing distributed relational data with graph, search, analytics, and multi-region options.
Redis Insight is suited to developers and administrators who work with Redis data and want GUI and command-line tools for inspection and management.
It suits organizations building operational applications from live geographic, sensor, satellite, or enterprise data.
It suits developers building flexible-schema, latency-sensitive, elastic, high-throughput, or highly available mission-critical applications.
AllegroGraph suits teams building graph-based applications that need querying, reasoning, or vector storage.
YBA suits teams operating YugabyteDB across on-premises infrastructure, public clouds or Kubernetes.