DBMS > Apache Druid vs. EDB Postgres vs. RethinkDB vs. RocksDB

System Properties Comparison Apache Druid vs. EDB Postgres vs. RethinkDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

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

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Document store

Key-value store

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	1.90
Rank	#135	Overall
	#63	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

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

Website

Technical documentation

druid.apache.org/docs/latest/design

www.enterprisedb.com/docs

rethinkdb.com/docs

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

EnterpriseDB

The Linux Foundation

since July 2017

Facebook, Inc.

Initial release

2012

2005

2009

2013

Current release

29.0.1, April 2024

14, December 2021

2.4.1, August 2020

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

BSD for PostgreSQL-components

Open Source

Apache Version 2

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

Linux
Windows

Linux
OS X
Windows

Linux

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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 for querying

yes

standard with numerous extensions

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

C
C++
Go
Java
Perl
Python
Ruby

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

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

horizontal partitioning

by hash, list or range

Sharding

range based

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-document operations

yes

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

MVCC based

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.

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

yes

users and table-level permissions

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