DBMS > CockroachDB vs. Fujitsu Enterprise Postgres vs. GeoSpock vs. Oracle Rdb vs. SQLite

System Properties Comparison CockroachDB vs. Fujitsu Enterprise Postgres vs. GeoSpock vs. Oracle Rdb vs. SQLite

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

CockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Spatial and temporal data processing engine for extreme data scale

Widely used embeddable, in-process RDBMS

Primary database model

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Time Series DBMS

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

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	0.37
Rank	#278	Overall
	#128	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.cockroachlabs.com

www.postgresql.fastware.com

geospock.com

www.oracle.com/database/technologies/related/rdb.html

www.sqlite.org

Technical documentation

www.cockroachlabs.com/docs

www.postgresql.fastware.com/product-manuals

www.oracle.com/database/technologies/related/rdb-doc.html

www.sqlite.org/docs.html

Developer

Cockroach Labs

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

GeoSpock

Oracle, originally developed by Digital Equipment Corporation (DEC)

Dwayne Richard Hipp

Initial release

2015

1984

2000

Current release

24.1.0, May 2024

Fujitsu Enterprise Postgres 14, January 2022

2.0, September 2019

7.4.1.1, 2021

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

Open Source

Public Domain

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, Javascript

Server operating systems

Linux
macOS
Windows

Linux
Windows

hosted

HP Open VMS

server-less

Data scheme

dynamic schema

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

temporal, categorical

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes

ANSI SQL for query only (using Presto)

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by key range)

all tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFT

partitioning by range, list and by hash

Automatic sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

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.

yes

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

Access rights for users can be defined per table

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