DBMS > Cubrid vs. Datomic vs. Google Cloud Spanner

System Properties Comparison Cubrid vs. Datomic vs. Google Cloud Spanner

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Editorial information provided by DB-Engines

Name

Description

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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.

Primary database model

Relational DBMS

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

Score	0.97
Rank	#192	Overall
	#88	Relational DBMS

Score	1.50
Rank	#148	Overall
	#68	Relational DBMS

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Website

cubrid.com (korean)
cubrid.org (english)

www.datomic.com

cloud.google.com/spanner

Technical documentation

cubrid.org/manuals

docs.datomic.com

cloud.google.com/spanner/docs

Developer

CUBRID Corporation, CUBRID Foundation

Cognitect

Google

Initial release

2008

2012

2017

Current release

11.0, January 2021

1.0.7180, July 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

limited edition free

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++, Java

Java, Clojure

Server operating systems

Linux
Windows

All OS with a Java VM

hosted

Data scheme

yes

Typing

predefined data types such as float or date

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

yes

Query statements complying to ANSI 2011

APIs and other access methods

ADO.NET
JDBC
ODBC
OLE DB

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

Supported programming languages

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Clojure
Java

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Transaction Functions

Triggers

yes

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

But extensive use of caching in the application peers

Multi-source replication with 3 replicas for regional instances.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

fine grained access rights according to SQL-standard

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

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More resources

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