DBMS > Datomic vs. HarperDB vs. Percona Server for MongoDB vs. Quasardb vs. RocksDB

System Properties Comparison Datomic vs. HarperDB vs. Percona Server for MongoDB vs. Quasardb vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

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

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Distributed, high-performance timeseries database

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

Primary database model

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

Score	1.66
Rank	#144	Overall
	#66	Relational DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	0.60
Rank	#246	Overall
	#39	Document stores

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

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

Website

www.datomic.com

www.harperdb.io

www.percona.com/mongodb/software/percona-server-for-mongodb

quasar.ai

rocksdb.org

Technical documentation

docs.datomic.com

docs.harperdb.io/docs

docs.percona.com/percona-distribution-for-mongodb

doc.quasar.ai/master

github.com/facebook/rocksdb/wiki

Developer

Cognitect

HarperDB

Percona

quasardb

Facebook, Inc.

Initial release

2012

2017

2015

2009

2013

Current release

1.0.6735, June 2023

3.1, August 2021

3.4.10-2.10, November 2017

3.14.1, January 2024

9.2.1, May 2024

License

Commercial or Open Source

commercial

limited edition free

commercial

free community edition available

Open Source

GPL Version 2

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

Open Source

BSD

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

Java, Clojure

Node.js

C++

Server operating systems

All OS with a Java VM

Linux
OS X

Linux

BSD
Linux
OS X
Windows

Linux

Data scheme

yes

dynamic schema

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

yes

integer and binary

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

with tags

SQL

Support of SQL

SQL-like data manipulation statements

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

proprietary protocol using JSON

HTTP API

C++ API
Java API

Supported programming languages

Clojure
Java

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Transaction Functions

Custom Functions

since release 3.1

JavaScript

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

A table resides as a whole on one (or more) nodes in a cluster

Sharding

consistent hashing

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

yes

the nodes on which a table resides can be defined

Source-replica replication

Source-replica replication with selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

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, using LMDB

yes

by using LevelDB

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

via In-Memory Engine

yes

Transient mode

yes

User concepts

Access control

Access rights for users and roles

Cryptographically strong user authentication and audit trail

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