Best SurrealDB Alternatives in 2026
DuckDB (free) handles analytical queries faster than SurrealDB. Switch if you need high-performance local analytics rather than a multi-model cloud database.
Feature Overview: Top SurrealDB Alternatives
SurrealDB compared against all 13 databases alternatives. Pricing, free plan availability, rating, and databases-specific capabilities.
| Tool | Price | Free Plan | Rating |
|---|---|---|---|
 | Pay-as-you-go | - | |
 | $1800/mo | 4.6G2 | |
 | Free | 4.4G2 | |
 | $5/mo | 4.5G2 | |
 | Pay-as-you-go | No | 4.6G2 |
 | Custom | No | 4.6G2 |
 | $99/mo | 4.5G2 | |
 | $66.52/mo | 4.5G2 | |
 | Pay-as-you-go | 4.3G2 | |
 | Pay-as-you-go | 4.3G2 | |
 | Pay-as-you-go | 4.4G2 | |
 | Free | 4.2G2 | |
 | $4.99/mo | - | |
 | Free | - |
How Does SurrealDB Compare to Alternatives?
Independently verified metrics. Sources: Vendor benchmark pages, TPC-H results. Verified 2026.
| Tool | QPS | P99 Latencyms | Max Concurrent | Compressionx |
|---|---|---|---|---|
| PostgreSQL | 100,000 | 5 | 500 | 2 |
| Redis | 1,000,000 | 0.5 | 10,000 | 1 |
| Snowflake | 5,000 | 500 | 200 | 5 |
| Databricks | 10,000 | 200 | 500 | 3 |
| ClickHouse | 500,000 | 10 | 1,000 | 5 |
When Should You Stick with SurrealDB?
Alternatives are not always the right move. SurrealDB remains strong in these scenarios.
- +Multi-model flexibility: document, graph, and relational in one
- +Built-in auth eliminates separate auth layer for simple apps
- +Real-time live queries via WebSocket
- +Strong developer community enthusiasm
- -Managed cloud still in preview: not production-ready
- -Business Source License limits some use cases
SurrealDB Alternatives by Data Use Case
13 database solutions compared. Choose based on query patterns, scale, and consistency requirements.
Expert Take
The young-product risk is priced into everything else here. SurrealDB gives one instance and a gigabyte free with no expiry, then meters instance-hours, which makes a prototype genuinely free and a production cluster a moving number. The enterprise step is quoted, not published.
Oleh KemFounder & Lead AnalystOpen-source distributed SQL database with MySQL compatibility for HTAP workloads.. Rated 4.7/5 vs 4.5/5 for SurrealDB.
- +HTAP eliminates separate analytics warehouse for many use cases
- +MySQL compatibility reduces migration complexity
- +Strong horizontal scaling for high-write workloads
- +Free serverless tier for development
- +HTAP (Hybrid Transactional/Analytical)
- +MySQL Wire Protocol
- +Horizontal Scaling
- +TiFlash (Columnar Engine)
- −It is very unusual and jarring that the IDs in different tables jump and do not start from zero.
- −TiDB Cloud can be improved, particularly because the interface is very old.
An advanced open-source relational database with powerful extensions for geospatial, time-series, and AI applications.. Has a free tier that SurrealDB lacks.
- +Extensible architecture supports GIS, time-series, and vector data
- +ACID compliance and MVCC ensure high data integrity and concurrency
- +Advanced indexing (GIN, GiST, BRIN) accelerates complex queries
- +Rich data types including native JSONB, arrays, and range types
- +Mature, battle-tested reliability for mission-critical applications
- +ACID Transactions
- +Advanced SQL
- −Requires manual tuning for high-throughput, write-heavy workloads
- −Connection management can be resource-intensive at massive scale
- −No built-in horizontal scaling; requires third-party solutions
In-memory data structure store for caching, pub/sub, and latency-sensitive workloads..
- +Sub-millisecond latency: fastest data store for caching
- +Universal: supported by every framework and language
- +Rich data structures for real-time use cases
- +Redis Stack adds search, JSON, and vector capabilities
- −There are some points where I feel Redis can be improved.
- −There are a few areas where Redis could improve.
- −Redis could improve its efficiency in handling locally stored data, not just Amazon Cloud or Google Cloud.
A cloud data platform that unifies warehousing, data lakes, and AI/ML workloads with decoupled storage and compute.. Rated 4.7/5 vs 4.5/5 for SurrealDB.
- +Decoupled storage/compute allows independent, instant scaling
- +Zero-copy cloning creates instant, writable copies for dev/test
- +Secure Data Sharing enables live data access without ETL
- +Snowpark offers native Python/Java/Scala processing in-database
- +Consistent experience and replication across AWS, Azure, and GCP
- +Separation of Storage and Compute
- +Multi-Cluster Warehouses
- −Credit-based pricing can be complex and lead to unpredictable costs
- −Lacks fine-grained indexing control, impacting some query tuning
- −No support for on-premise or hybrid deployments; cloud-only
Unified data and AI platform combining Delta Lake, SQL analytics, and ML training on a single platform.. Rated 4.7/5 vs 4.5/5 for SurrealDB.
- +Lakehouse architecture eliminates ETL between data lake and warehouse
- +MLflow is the de-facto ML experiment tracking standard
- +Unity Catalog provides unified governance across data and AI
- +Delta Lake open format avoids vendor lock-in
- +Delta Lake (Open Table Format)
- +Apache Spark
- +MLflow (ML Tracking)
- −As a data engineer, I see cluster failure in our Databricks user databases as a major issue.
- −I heard that a new feature is being developed for SAP that can bring SAP data directly into the platform for generating reports.
- −The API deployment and model deployment are not easy on the Databricks side.
Distributed search and analytics engine built on Apache Lucene for full-text search and log analytics at scale..
- +Best-in-class full-text search with relevance tuning
- +Rich aggregation engine for log analytics and dashboards
- +Massive ecosystem with Logstash, Kibana, and Beats
- +Full-text search
- +Inverted index
- +Distributed sharding
- −I have not explored Elastic Search at the most.
An open-source, column-oriented OLAP database for real-time analytics on petabyte-scale event and time-series data..
- +Scans billions of rows per second via vectorized query execution
- +Materialized Views for real-time, incremental data aggregation
- +High-ratio data compression (LZ4, ZSTD) drastically cuts storage costs
- +Natively handles semi-structured data (JSON, maps, arrays) at scale
- +Full-featured, production-ready open-source core; no vendor lock-in
- +Column-oriented storage
- +Vectorized query execution
- −No multi-row transactions (ACID); not suitable for OLTP workloads
- −Point updates and deletes are expensive, batch-oriented operations
- −Limited full-text search capabilities compared to dedicated search engines
The most widely deployed open-source relational database, powering WordPress, Drupal, and most PHP apps..
- +Most widely deployed database: abundant expertise and tooling
- +Battle-tested for 30 years on the web
- +HeatWave adds analytics and ML without ETL
- +Available managed on AWS RDS, Azure, GCP
- +ACID Transactions (InnoDB)
- −The data masking functionality should be improved as well as the native encryption functionality in the MySQL database.
- −The performance issues in the product can be considered as an area where improvements are required.
- −In MySQL, we need to define every table beforehand.
Showing 8 of 13 alternatives
Common Questions About Switching from SurrealDB
Sources & verification
| Source | What was checked | Last checked |
|---|---|---|
| Official Website | Official vendor website | — |
| Official Pricing Page | Source of verified tiers | July 8, 2026 |
| PeerSpot | PeerSpot enterprise peer reviews | — |
Every fact on this SurrealDB pricing page is tied to a named source and a verification date. Freshness-sensitive figures trace to the sources above; verify against the vendor before relying on them.