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SurrealDB software alternatives

Best SurrealDB Alternatives in 2026

Updated May 30, 2026 · 13 ranked

DuckDB (free) handles analytical queries faster than SurrealDB. Switch if you need high-performance local analytics rather than a multi-model cloud database.

Quick Verdict
Best overall4.8G2
Best value4.6G2
Snowflake logo
Snowflake
Pay-as-you-goReview →

How Does SurrealDB Compare to Alternatives?

Independently verified metrics. Sources: Vendor benchmark pages, TPC-H results. Verified 2026.

ToolQPSP99 LatencymsMax ConcurrentCompressionx
PostgreSQL100,00055002
Redis1,000,0000.510,0001
Snowflake5,0005002005
Databricks10,0002005003
QPS: Queries per second at standard benchmark workload.P99 Latency: P99 query latency. Benchmark <20ms.Max Concurrent: Simultaneous analytical queries without performance degradation.Compression: Data compression ratio (e.g., 3x means 3× storage savings).


When Should You Stick with SurrealDB?

Alternatives are not always the right move. SurrealDB remains strong in these scenarios.

Stick with SurrealDB if you need
  • +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
Consider an alternative when
  • -Managed cloud still in preview: not production-ready
  • -Business Source License limits some use cases
Before You Switch: 5-Step Migration Checklist
1Export your SurrealDB data — documents, settings, templates, and API credentials
2Audit all integrations and automations built on SurrealDB
3Run a 2-week parallel trial on a non-critical workflow before cancelling SurrealDB
4Calculate true cost delta: include retraining time + data migration, not just subscription price
5Confirm the alternative covers your primary use case — a lower price is worthless if core workflows break

SurrealDB Alternatives by Data Use Case

13 database solutions compared. Choose based on query patterns, scale, and consistency requirements.

Expert Take

SurrealDB works well when developers need to unify document, graph, and relational data models into a single engine with real-time live queries. The friction starts when users encounter high memory usage, key ordering issues, and poor performance under load. Before buying, compare vs PostgreSQL, a mature relational database that handles complex queries without the memory overhead of SurrealDB's multi-model architecture.

·Oleh KemOleh KemFounder & Lead Analyst
DuckDB logo
DuckDB4.8G2
DatabaseFree

In-process analytical database that runs inside Python, R, or any application, with no server required.. Has a free tier that SurrealDB lacks.

Why Choose DuckDB
  • +Runs in-process with zero infrastructure setup
  • +Directly queries Parquet and CSV on S3 without ETL
  • +Outperforms many server-based DBs on single-machine workloads
  • +In-process execution
  • +Parquet/CSV/JSON direct query
  • +S3 and GCS file access
Points of Friction
  • Sometimes we have memory issues that cause job failures, which we don't fully understand why, but we can rerun the jobs without pr
TiDB logo
TiDB4.6G2
DatabaseFrom $317/mo

Open-source distributed SQL database with MySQL compatibility for HTAP workloads..

Why Choose TiDB
  • +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)
Points of Friction
  • 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.
PostgreSQL logo
DatabaseFree

An advanced open-source relational database with powerful extensions for geospatial, time-series, and AI applications.. Has a free tier that SurrealDB lacks.

Why Choose PostgreSQL
  • +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
Points of Friction
  • 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
Redis logo
Redis4.5G2
DatabaseFrom $5/mo

In-memory data structure store for caching, pub/sub, and latency-sensitive workloads..

Why Choose Redis
  • +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
Points of Friction
  • 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.
Snowflake logo
DatabasePay-as-you-go

A cloud data platform that unifies warehousing, data lakes, and AI/ML workloads with decoupled storage and compute..

Why Choose Snowflake
  • +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
Points of Friction
  • 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
Databricks logo
DatabasePay-as-you-go

Unified data and AI platform combining Delta Lake, SQL analytics, and ML training on a single platform..

Why Choose Databricks
  • +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)
Points of Friction
  • 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.
Elasticsearch logo
DatabaseFrom $99/mo

Distributed search and analytics engine built on Apache Lucene for full-text search and log analytics at scale..

Why Choose Elasticsearch
  • +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
Points of Friction
  • I have not explored Elastic Search at the most.
ClickHouse logo
DatabasePay-as-you-go

An open-source, column-oriented OLAP database for real-time analytics on petabyte-scale event and time-series data..

Why Choose ClickHouse
  • +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
Points of Friction
  • 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

Showing 8 of 13 alternatives



Key Differences: SurrealDB vs. Top Alternatives

SurrealDB compared against all 13 databases alternatives. Pricing, free plan availability, rating, and databases-specific capabilities.

ToolPriceFree PlanRating
SurrealDB logo
SurrealDByou
Pay-as-you-go-
DuckDB logo
DuckDB
Free4.8G2
TiDB logo
TiDB
$317/mo4.6G2
PostgreSQL logo
PostgreSQL
Free4.4G2
Redis logo
Redis
$5/mo4.5G2
Snowflake logo
Snowflake
Pay-as-you-goNo4.6G2
Databricks logo
Databricks
Pay-as-you-go4.6G2
Elasticsearch logo
Elasticsearch
$99/mo4.5G2
ClickHouse logo
ClickHouse
Pay-as-you-go4.5G2
MySQL logo
MySQL
Pay-as-you-go4.3G2
CockroachDB logo
CockroachDB
Pay-as-you-go4.3G2
Oracle Database 23ai logo
Oracle Database 23ai
Pay-as-you-go4.4G2
OpenSearch logo
OpenSearch
Free4.2G2
Turso logo
Turso
Pay-as-you-go-

Top-Rated SurrealDB Alternatives

#1 Top PickDatabase
DuckDB logo
DuckDB4.8G2

Choose DuckDB if you need runs in-process with zero infrastructure setup

FreeFree plan
#2 Runner-UpDatabase
TiDB logo
TiDB4.6G2

Choose TiDB if you need htap eliminates separate analytics warehouse for many use cases

$317/moFree plan
#3 Strong ChoiceDatabase

Choose PostgreSQL if you need #1 most-loved database: massive community and ecosystem

FreeFree plan

Oleh KemOleh KemFounder & Lead AnalystExpert verified·Updated May 30, 2026·Our methodology
Price & Data Intelligence SyncLast verified: May 30, 2026 · CE-DB-2026W23-977363 · ✓ Pricing updated May 30, 2026
Up to date

Common Questions About Switching from SurrealDB



Sources & Data Trail · SurrealDB

  1. 1.Official Website·Official vendor website
  2. 2.Official Pricing Page·Source of verified tiers(Checked: 2026-05-30)
  3. 3.PeerSpot·PeerSpot enterprise peer reviews