DBMS > ArcadeDB vs. Citus vs. CockroachDB vs. Drizzle vs. Google Cloud Spanner

System Properties Comparison ArcadeDB vs. Citus vs. CockroachDB vs. Drizzle vs. Google Cloud Spanner

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Primary database model

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

Secondary database models

Document store

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

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	6.15
Rank	#55	Overall
	#33	Relational DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Website

arcadedb.com

www.citusdata.com

www.cockroachlabs.com

cloud.google.com/spanner

Technical documentation

docs.arcadedb.com

docs.citusdata.com

www.cockroachlabs.com/docs

cloud.google.com/spanner/docs

Developer

Arcade Data

Cockroach Labs

Drizzle project, originally started by Brian Aker

Google

Initial release

2021

2010

2015

2008

2017

Current release

September 2021

8.1, December 2018

24.1.0, May 2024

7.2.4, September 2012

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

AGPL, commercial license also available

Open Source

Apache 2.0, commercial license available

Open Source

GNU GPL

commercial

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

C++

Server operating systems

All OS with a Java VM

Linux

Linux
macOS
Windows

FreeBSD
Linux
OS X

hosted

Data scheme

schema-free

yes

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

specific XML type available, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language, no joins

yes

standard, with numerous extensions

yes, wire compatible with PostgreSQL

yes

with proprietary extensions

yes

Query statements complying to ANSI 2011

APIs and other access methods

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

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

JDBC

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

Supported programming languages

Java

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

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

C
C++
Java
PHP

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Triggers

yes

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Multi-source replication using RAFT

Multi-source replication
Source-replica replication

Multi-source replication with 3 replicas for regional instances.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

relationship in graphs

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

Transaction concepts

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

ACID

Strict serializable isolation

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

fine grained access rights according to SQL-standard

Role-based access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

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1 July 2013, Matthias Gelbmann

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