DBMS > Apache Druid vs. EJDB vs. Lovefield vs. OrigoDB vs. Sequoiadb

System Properties Comparison Apache Druid vs. EJDB vs. Lovefield vs. OrigoDB vs. Sequoiadb

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

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

Embeddable relational database for web apps written in pure JavaScript

A fully ACID in-memory object graph database

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS
Time Series DBMS

Document store

Relational DBMS

Document store
Object oriented DBMS

Document store
Relational DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

druid.apache.org

github.com/Softmotions/ejdb

google.github.io/lovefield

origodb.com

www.sequoiadb.com

Technical documentation

druid.apache.org/docs/latest/design

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

github.com/google/lovefield/blob/master/docs/spec_index.md

origodb.com/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Apache Software Foundation and contributors

Softmotions

Google

Robert Friberg et al

Sequoiadb Ltd.

Initial release

2012

2014

2009

under the name LiveDB

2013

Current release

29.0.1, April 2024

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

GPLv2

Open Source

Apache 2.0

Open Source

Server: AGPL; Client: Apache V2

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

JavaScript

C++

Server operating systems

Linux
OS X
Unix

server-less

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
Windows

Linux

Data scheme

yes

schema-less columns are supported

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

User defined using .NET types and collections

yes

oid, date, timestamp, binary, regex

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

SQL-like query language

via JavaScript builder pattern

SQL-like query language

APIs and other access methods

JDBC
RESTful HTTP/JSON API

in-process shared library

.NET Client API
HTTP API
LINQ

proprietary protocol using JSON

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

.Net

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

Using read-only observers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

horizontal partitioning

client side managed; servers are not synchronized

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

depending on model

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

Write ahead log

yes

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

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

Role based authorization

simple password-based access control

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, Datanami

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

'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 | by Zisis Flokas
18 October 2021, Towards Data Science

provided by Google News

Share this page