DBMS > Fauna vs. IBM Db2 Event Store vs. JaguarDB vs. MySQL vs. Sphinx

System Properties Comparison Fauna vs. IBM Db2 Event Store vs. JaguarDB vs. MySQL vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Distributed Event Store optimized for Internet of Things use cases

Performant, highly scalable DBMS for AI and IoT applications

Widely used open source RDBMS

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Event Store
Time Series DBMS

Key-value store
Vector DBMS

Relational DBMS

Key/Value like access via memcached API

Search engine

Secondary database models

Document store
Spatial DBMS

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

Score	1.55
Rank	#151	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	0.27
Rank	#309	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	0.06
Rank	#381	Overall
	#59	Key-value stores
	#15	Vector DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

fauna.com

www.ibm.com/products/db2-event-store

www.jaguardb.com

www.mysql.com

sphinxsearch.com

Technical documentation

docs.fauna.com

www.ibm.com/docs/en/db2-event-store

www.jaguardb.com/support.html

dev.mysql.com/doc

sphinxsearch.com/docs

Developer

Fauna, Inc.

IBM

DataJaguar, Inc.

Oracle

since 2010, originally MySQL AB, then Sun

Sphinx Technologies Inc.

Initial release

2014

2017

2015

1995

2001

Current release

2.0

3.3 July 2023

8.4.0, April 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

free developer edition available

Open Source

GPL V3.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL version 2, commercial licence available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Scala

C and C++

C++

the server part. Clients available in other languages

C and C++

C++

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

Linux

FreeBSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

full-text index on all search fields

SQL

Support of SQL

yes

through the embedded Spark runtime

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

with proprietary extensions

SQL-like query language (SphinxQL)

APIs and other access methods

RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Active-active shard replication

Multi-source replication

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes

User concepts

Access control

Identity management, authentication, and access control

fine grained access rights according to SQL-standard

rights management via user accounts

Users with fine-grained authorization concept

no user groups or roles

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