DBMS > CockroachDB vs. Coveo vs. EsgynDB vs. RocksDB vs. TimescaleDB

System Properties Comparison CockroachDB vs. Coveo vs. EsgynDB vs. RocksDB vs. TimescaleDB

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.

AI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code development

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Relational DBMS

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

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	2.11
Rank	#118	Overall
	#11	Search engines

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

www.cockroachlabs.com

Technical documentation

www.cockroachlabs.com/docs

docs.coveo.com

github.com/facebook/rocksdb/wiki

docs.timescale.com

Developer

Cockroach Labs

Coveo

Esgyn

Facebook, Inc.

Timescale

Initial release

2015

2012

2015

2013

2017

Current release

24.1.0, May 2024

9.2.1, May 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

Open Source

BSD

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

C++, Java

C++

Server operating systems

Linux
macOS
Windows

hosted

Linux

Linux
OS X
Windows

Data scheme

dynamic schema

hybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configuration

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC

RESTful HTTP API

ADO.NET
JDBC
ODBC

C++ API
Java API

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

Supported programming languages

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

C#
Java
JavaScript
Python

All languages supporting JDBC/ODBC/ADO.Net

C
C++
Go
Java
Perl
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java Stored Procedures

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

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

yes

Sharding

horizontal partitioning

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

yes

Multi-source replication between multi datacenters

yes

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

ACID

yes

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.

yes

User concepts

Access control

Role-based access control

granular access controls, API key management, content filters

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.