DBMS > CockroachDB vs. KeyDB vs. RocksDB vs. SAP SQL Anywhere vs. TigerGraph

System Properties Comparison CockroachDB vs. KeyDB vs. RocksDB vs. SAP SQL Anywhere vs. TigerGraph

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.

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

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

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

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

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Score	1.83
Rank	#139	Overall
	#13	Graph DBMS

Website

www.cockroachlabs.com

github.com/Snapchat/KeyDB
keydb.dev

rocksdb.org

www.sap.com/products/technology-platform/sql-anywhere.html

www.tigergraph.com

Technical documentation

www.cockroachlabs.com/docs

docs.keydb.dev

github.com/facebook/rocksdb/wiki

help.sap.com/docs/SAP_SQL_Anywhere

docs.tigergraph.com

Developer

Cockroach Labs

EQ Alpha Technology Ltd.

Facebook, Inc.

SAP

formerly Sybase

Initial release

2015

2019

2013

1992

2017

Current release

23.1.1, May 2023

8.11.4, April 2024

17, July 2015

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

Open Source

BSD-3

Open Source

BSD

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.

Implementation language

C++

Server operating systems

Linux
macOS
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

yes

SQL-like query language (GSQL)

APIs and other access methods

JDBC

Proprietary protocol

RESP - REdis Serialization Protoco

C++ API
Java API

ADO.NET
HTTP API
JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

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

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C
C++
Go
Java
Perl
Python
Ruby

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

C++
Java

Server-side scripts

Stored procedures

Lua

yes, in C/C++, Java, .Net or Perl

yes

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

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

Multi-source replication
Source-replica replication

yes

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

simple password-based access control and ACL

fine grained access rights according to SQL-standard

Role-based access control

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