DBMS > Fauna vs. GridDB vs. IBM Db2 Event Store vs. SQLite

System Properties Comparison Fauna vs. GridDB vs. IBM Db2 Event Store vs. SQLite

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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.

Scalable in-memory time series database optimized for IoT and Big Data

Distributed Event Store optimized for Internet of Things use cases

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Time Series DBMS

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Key-value store
Relational 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	2.09
Rank	#120	Overall
	#10	Time Series DBMS

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

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

fauna.com

griddb.net

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

www.sqlite.org

Technical documentation

docs.fauna.com

docs.griddb.net

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

www.sqlite.org/docs.html

Developer

Fauna, Inc.

Toshiba Corporation

IBM

Dwayne Richard Hipp

Initial release

2014

2013

2017

2000

Current release

5.1, August 2022

2.0

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

free developer edition available

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Scala

C++

C and C++

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

not rigid because of 'dynamic typing' concept.

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

SQL92, SQL-like TQL (Toshiba Query Language)

yes

through the embedded Spark runtime

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

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

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

Active-active shard replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID at container level

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

via file-system locks

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

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.