DBMS > CockroachDB vs. Elasticsearch vs. MySQL vs. SpaceTime

System Properties Comparison CockroachDB vs. Elasticsearch vs. MySQL vs. SpaceTime

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Editorial information provided by DB-Engines

Name

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.

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

Widely used open source RDBMS

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

Relational DBMS

Search engine

Relational DBMS

Key/Value like access via memcached API

Spatial DBMS

Secondary database models

Document store
Spatial DBMS
Vector DBMS

Document store
Spatial DBMS

Relational DBMS

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	135.35
Rank	#7	Overall
	#1	Search engines

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

www.cockroachlabs.com

www.elastic.co/elasticsearch

www.mysql.com

www.mireo.com/spacetime

Technical documentation

www.cockroachlabs.com/docs

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

dev.mysql.com/doc

Developer

Cockroach Labs

Elastic

Oracle

since 2010, originally MySQL AB, then Sun

Mireo

Initial release

2015

2010

1995

2020

Current release

23.1.1, May 2023

8.6, January 2023

8.4.0, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

Open Source

Elastic License

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Java

C and C++

C++

Server operating systems

Linux
macOS
Windows

All OS with a Java VM

FreeBSD
Linux
OS X
Solaris
Windows

Linux

Data scheme

dynamic schema

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

SQL-like query language

yes

with proprietary extensions

A subset of ANSI SQL is implemented

APIs and other access methods

JDBC

Java API
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

RESTful HTTP API

Supported programming languages

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

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C#
C++
Python

Server-side scripts

Stored procedures

yes

proprietary syntax

Triggers

yes

by using the 'percolation' feature

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

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

yes

Multi-source replication
Source-replica replication

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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.

Memcached and Redis integration

yes

User concepts

Access control

Role-based access control

Users with fine-grained authorization concept

no user groups or roles

yes

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