DBMS > CockroachDB vs. Datomic vs. IBM Cloudant vs. RocksDB vs. Sqrrl

System Properties Comparison CockroachDB vs. Datomic vs. IBM Cloudant vs. RocksDB vs. Sqrrl

Editorial information provided by DB-Engines

Name

Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed 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.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Database as a Service offering based on Apache CouchDB

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

Adaptable, secure NoSQL built on Apache Accumulo

Primary database model

Relational DBMS

Document store

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

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

Score	5.73
Rank	#58	Overall
	#34	Relational DBMS

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	2.75
Rank	#104	Overall
	#19	Document stores

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

Website

www.cockroachlabs.com

www.datomic.com

www.ibm.com/products/cloudant

rocksdb.org

sqrrl.com

Technical documentation

www.cockroachlabs.com/docs

docs.datomic.com

cloud.ibm.com/docs/Cloudant

github.com/facebook/rocksdb/wiki

Developer

Cockroach Labs

Cognitect

IBM, Apache Software Foundation

IBM acquired Cloudant in February 2014

Facebook, Inc.

Amazon

originally Sqrrl Data, Inc.

Initial release

2015

2012

2010

2013

2012

Current release

24.1.0, May 2024

1.0.6735, June 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0, commercial license available

commercial

limited edition free

commercial

Open Source

BSD

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, Clojure

Erlang

C++

Java

Server operating systems

Linux
macOS
Windows

All OS with a Java VM

hosted

Linux

Data scheme

dynamic schema

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

yes, wire compatible with PostgreSQL

APIs and other access methods

JDBC

RESTful HTTP API

RESTful HTTP/JSON API

C++ API
Java API

Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift

Supported programming languages

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

Clojure
Java

C#
Java
JavaScript
Objective-C
PHP
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Actionscript
C

using GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk

Server-side scripts

Stored procedures

yes

Transaction Functions

View functions (Map-Reduce) in JavaScript

Triggers

By using transaction functions

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

none

But extensive use of caching in the application peers

Sharding

horizontal partitioning

Sharding

making use of Hadoop

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication using RAFT

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

yes

selectable replication factor

making use of Hadoop

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

Immediate Consistency

Document store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a document possible

yes

Atomic updates per row, document, or graph entity

Concurrency

Support for concurrent manipulation of data

yes

Optimistic locking

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

Role-based access control

Access rights for users can be defined per database

Cell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)

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