DBMS > Apache Druid vs. Badger vs. EJDB vs. JSqlDb vs. RocksDB

System Properties Comparison Apache Druid vs. Badger vs. EJDB vs. JSqlDb vs. RocksDB

Editorial information provided by DB-Engines

Name

JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

JavaScript Query Language Database, stores JavaScript objects and primitives

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

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Document store

Document store
Object oriented DBMS

Key-value store

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

Score	2.85
Rank	#96	Overall
	#50	Relational DBMS
	#6	Time Series DBMS

Score	0.14
Rank	#328	Overall
	#48	Key-value stores

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Website

druid.apache.org

github.com/dgraph-io/badger

github.com/Softmotions/ejdb

jsqldb.org (offline)

rocksdb.org

Technical documentation

druid.apache.org/docs/latest/design

godoc.org/github.com/dgraph-io/badger

github.com/Softmotions/ejdb/blob/master/README.md

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

DGraph Labs

Softmotions

Konrad von Backstrom

Facebook, Inc.

Initial release

2012

2017

2012

2018

2013

Current release

30.0.0, June 2024

0.8, December 2018

9.4.0, June 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

GPLv2

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

C++

Server operating systems

Linux
OS X
Unix

BSD
Linux
OS X
Solaris
Windows

server-less

Linux
macOS
Windows

Linux

Data scheme

yes

schema-less columns are supported

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

SQL for querying

APIs and other access methods

JDBC
RESTful HTTP/JSON API

in-process shared library

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

JavaScript

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

functions in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

yes

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

using RocksDB

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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Apache® Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers’ Choice Awards
26 January 2024, Business Wire

Imply Announces the Availability of Imply Polaris, a Database-as-a-Service Built from Apache Druid, on Microsoft Azure
26 June 2024, Yahoo Finance

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

Apache Druid Takes Its Place In The Pantheon Of Databases
16 June 2022, The Next Platform

How to connect DataGrip to Apache Druid
18 October 2021, Towards Data Science

provided by Google News

Dgraph raises $11.5 million for scalable graph database solutions
31 July 2019, VentureBeat

provided by Google News

AMD EPYC vs. Intel Xeon Cascadelake With Facebook's RocksDB Database
17 October 2019, Phoronix

Pliops Unveils Accelerated Key-Value Store That Boosts RocksDB Performance by 20x at OCP Global Summit
18 October 2022, GlobeNewswire

Did Rockset Just Solve Real-Time Analytics?
25 August 2021, Datanami

Meta’s Velox Means Database Performance Is Not Subject To Interpretation
31 August 2022, The Next Platform

Facebook’s MyRocks Truly Rocks!
21 September 2020, Open Source For You

provided by Google News

Share this page