DBMS > Datomic vs. GeoSpock vs. KeyDB vs. RocksDB vs. SWC-DB

System Properties Comparison Datomic vs. GeoSpock vs. KeyDB vs. RocksDB vs. SWC-DB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Spatial and temporal data processing engine for extreme data scale

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)

A high performance, scalable Wide Column DBMS

Primary database model

Relational DBMS

Key-value store

Wide column store

Secondary database models

Time Series DBMS

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

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

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

www.datomic.com

geospock.com

github.com/Snapchat/KeyDB
keydb.dev

rocksdb.org

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

docs.datomic.com

docs.keydb.dev

github.com/facebook/rocksdb/wiki

Developer

Cognitect

GeoSpock

EQ Alpha Technology Ltd.

Facebook, Inc.

Alex Kashirin

Initial release

2012

2019

2013

2020

Current release

1.0.7075, December 2023

2.0, September 2019

9.2.1, May 2024

0.5, April 2021

License

Commercial or Open Source

commercial

limited edition free

commercial

Open Source

BSD-3

Open Source

BSD

Open Source

GPL V3

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

Java, Javascript

C++

Server operating systems

All OS with a Java VM

hosted

Linux

Data scheme

yes

schema-free

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

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

temporal, categorical

yes

by using the Redis Search module

SQL

Support of SQL

ANSI SQL for query only (using Presto)

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC

Proprietary protocol

RESP - REdis Serialization Protoco

C++ API
Java API

Proprietary protocol
Thrift

Supported programming languages

Clojure
Java

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++

Server-side scripts

Stored procedures

yes

Transaction Functions

Lua

Triggers

By using transaction functions

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Automatic sharding

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Transaction concepts

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

ACID

Optimistic locking, atomic execution of commands blocks and scripts

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

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

recommended only for testing and development

yes

User concepts

Access control

Access rights for users can be defined per table

simple password-based access control and ACL

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