DBMS > Axibase vs. Google Cloud Spanner vs. OushuDB vs. SurrealDB

System Properties Comparison Axibase vs. Google Cloud Spanner vs. OushuDB vs. SurrealDB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Time Series DBMS

Relational DBMS

Document store
Graph DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.22
Rank	#305	Overall
	#25	Time Series DBMS

Score	2.56
Rank	#97	Overall
	#50	Relational DBMS

Score	0.00
Rank	#380	Overall
	#156	Relational DBMS

Score	1.08
Rank	#176	Overall
	#30	Document stores
	#16	Graph DBMS

Website

axibase.com/docs/atsd/finance

cloud.google.com/spanner

www.oushu.com/product/oushuDB

surrealdb.com

Technical documentation

cloud.google.com/spanner/docs

www.oushu.com/documentation

surrealdb.com/docs

Developer

Axibase Corporation

Google

Oushu

SurrealDB Ltd

Initial release

2013

2017

2022

Current release

15585

4.0.1, August 2020

v1.5.0, May 2024

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

commercial

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Rust

Server operating systems

Linux

hosted

Linux

Linux
macOS
Windows

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

Query statements complying to ANSI 2011

Full-featured ANSI SQL support

SQL-like query language

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

Go
Java
PHP
Python
R
Ruby

Go
Java
JavaScript (Node.js)
Python

C
C++

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication with 3 replicas for regional instances.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Kerberos, SSL and role based access

yes, based on authentication and database rules

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