DBMS > CockroachDB vs. GeoSpock vs. Postgres-XL vs. Trafodion

System Properties Comparison CockroachDB vs. GeoSpock vs. Postgres-XL vs. Trafodion

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

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

Apache Trafodion has been retired in 2021. Therefore it is 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.

Spatial and temporal data processing engine for extreme data scale

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Transactional SQL-on-Hadoop DBMS

Primary database model

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Website

www.cockroachlabs.com

geospock.com

www.postgres-xl.org

trafodion.apache.org

Technical documentation

www.cockroachlabs.com/docs

www.postgres-xl.org/documentation

trafodion.apache.org/documentation.html

Developer

Cockroach Labs

GeoSpock

Apache Software Foundation, originally developed by HP

Initial release

2015

2014

since 2012, originally named StormDB

2014

Current release

23.1.1, May 2023

2.0, September 2019

10 R1, October 2018

2.3.0, February 2019

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

Open Source

Mozilla public license

Open Source

Apache 2.0

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

C++, Java

Server operating systems

Linux
macOS
Windows

hosted

Linux
macOS

Linux

Data scheme

dynamic schema

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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

temporal, categorical

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

ANSI SQL for query only (using Presto)

yes

distributed, parallel query execution

yes

APIs and other access methods

JDBC

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

ADO.NET
JDBC
ODBC

Supported programming languages

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

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

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures

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

Automatic sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

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

MVCC

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

Role-based access control

Access rights for users can be defined per table

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Cockroach Labs Deepens Partnership with Google Cloud, CockroachDB Selected to Join Google Distributed Cloud
9 April 2024, PR Newswire

How DoorDash Migrated from Aurora Postgres to CockroachDB
5 December 2023, The New Stack

DoorDash Uses CockroachDB to Create Config Management Platform for Microservices
14 February 2024, InfoQ.com

How to Unlock Real-Time Data Streams with CockroachDB and Amazon MSK | Amazon Web Services
6 November 2023, AWS Blog

CockroachDB tempts legacy databases to crawl into the cloud age
29 January 2024, The Register

provided by Google News

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, VanillaPlus

nChain leads investment round in extreme-scale data firm GeoSpock
2 October 2020, CoinGeek

GeoSpock’s extreme-scale data mission in $5.4m funding boost
8 October 2020, Cambridge Independent

Big data processing techniques to streamline analytics
5 October 2018, TechTarget

The most promising deep tech startups of Cambridge in 2021
10 May 2021, UKTN (UK Technology News

provided by Google News

Evaluating HTAP Databases for Machine Learning Applications
2 November 2016, KDnuggets

Low-latency, distributed database architectures are critical for emerging fog applications
7 April 2022, Embedded Computing Design

provided by Google News

Share this page