DBMS > DataFS vs. Fauna vs. GeoMesa vs. Ignite vs. Trafodion

System Properties Comparison DataFS vs. Fauna vs. GeoMesa vs. Ignite vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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.

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Transactional SQL-on-Hadoop DBMS

Primary database model

Object oriented DBMS

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Spatial DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Graph DBMS

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

Score	0.09
Rank	#360	Overall
	#17	Object oriented DBMS

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

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Website

Technical documentation

dev.mobiland.com/Overview.xsp

docs.fauna.com

www.geomesa.org/documentation/stable/user/index.html

apacheignite.readme.io/docs

trafodion.apache.org/documentation.html

Developer

Mobiland AG

Fauna, Inc.

CCRi and others

Apache Software Foundation

Apache Software Foundation, originally developed by HP

Initial release

2018

2014

2015

2014

Current release

1.1.263, October 2022

5.0.0, May 2024

Apache Ignite 2.6

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache 2.0

Open Source

Apache 2.0

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++, Java, .Net

C++, Java

Server operating systems

Windows

hosted

Linux
OS X
Solaris
Windows

Linux

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
C
C#
C++
VB.Net

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C#
C++
Java
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions

yes (compute grid and cache interceptors can be used instead)

Java Stored Procedures

Triggers

no, except callback-events from server when changes happened

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

horizontal partitioning

consistent hashing

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

depending on storage layer

yes (replicated cache)

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

yes (compute grid and hadoop accelerator)

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

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.

depending on storage layer

yes

User concepts

Access control

Windows-Profile

Identity management, authentication, and access control

yes

depending on the DBMS used for storage

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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