DBMS > EJDB vs. MySQL vs. Sequoiadb vs. Solr vs. TypeDB

System Properties Comparison EJDB vs. MySQL vs. Sequoiadb vs. Solr vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

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

Widely used open source RDBMS

NewSQL database with distributed OLTP and SQL

A widely used distributed, scalable search engine based on Apache Lucene

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Document store
Relational DBMS

Search engine

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Document store
Spatial DBMS

Spatial DBMS

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

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

Score	41.02
Rank	#24	Overall
	#3	Search engines

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Website

github.com/Softmotions/ejdb

Technical documentation

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

dev.mysql.com/doc

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

solr.apache.org/resources.html

typedb.com/docs

Developer

Softmotions

Oracle

since 2010, originally MySQL AB, then Sun

Sequoiadb Ltd.

Apache Software Foundation

Vaticle

Initial release

2012

1995

2013

2006

2016

Current release

8.4.0, April 2024

9.6.0, April 2024

2.26.3, January 2024

License

Commercial or Open Source

Open Source

GPLv2

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache Version 2

Open Source

GPL Version 3, commercial licenses available

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.

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Implementation language

C and C++

C++

Java

Server operating systems

server-less

FreeBSD
Linux
OS X
Solaris
Windows

Linux

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

oid, date, timestamp, binary, regex

yes

supports customizable data types and automatic typing

yes

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

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language

Solr Parallel SQL Interface

APIs and other access methods

in-process shared library

ADO.NET
JDBC
ODBC
Proprietary native API

proprietary protocol using JSON

Java API
RESTful HTTP/JSON API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C++
Java
PHP
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

yes

proprietary syntax

JavaScript

Java plugins

Triggers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Source-replica replication

yes

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

not for MyISAM storage engine

substituted by the relationship feature

Transaction concepts

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

ACID

not for MyISAM storage engine

Document is locked during a transaction

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept

no user groups or roles

simple password-based access control

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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