DBMS > Apache Jena - TDB vs. etcd vs. Faircom DB vs. Informix

System Properties Comparison Apache Jena - TDB vs. etcd vs. Faircom DB vs. Informix

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena framework

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

A secure embeddable database from IBM, positioned besides IBM Db2 as a relatively low-cost product optimized for OLTP and Internet of Things data

Primary database model

RDF store

Key-value store

Key-value store
Relational DBMS

Relational DBMS

Since Version 12.10 support for JSON/BSON datatypes compatible with MongoDB

Secondary database models

Document store
Spatial DBMS
Time Series DBMS

with Informix TimeSeries Extension

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

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	17.12
Rank	#34	Overall
	#21	Relational DBMS

Website

jena.apache.org/documentation/tdb/index.html

etcd.io
github.com/etcd-io/etcd

www.faircom.com/products/faircom-db

www.ibm.com/products/informix

Technical documentation

jena.apache.org/documentation/tdb/index.html

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

Developer

Apache Software Foundation

originally developed by HP Labs

FairCom Corporation

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Initial release

2000

1979

1984

Current release

4.9.0, July 2023

3.4, August 2019

V12, November 2020

14.10.FC5, November 2020

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

Open Source

Apache Version 2.0

commercial

Restricted, free version available

commercial

free developer edition 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.

Implementation language

Java

ANSI C, C++

C, C++ and Java

Server operating systems

All OS with a Java VM

FreeBSD
Linux
Windows

experimental

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

AIX
HP-UX
Linux
macOS
Solaris
Windows

Data scheme

yes

RDF Schemas

schema-free

schema free, schema optional, schema required, partial schema,

yes

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

yes

Since Version 12.10 support for JSON/BSON datatypes

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

yes, ANSI SQL with proprietary extensions

yes

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

gRPC
JSON over HTTP

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

Supported programming languages

Java

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

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

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

yes

Triggers

yes

via event handler

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

Multi-source replication
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
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

TDB Transactions

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Yes, tunable from durable to delayed durability to in-memory

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

Access control via Jena Security

Fine grained access rights according to SQL-standard with additional protections for files

Users with fine-grained authentication, authorization, and auditing controls

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

Sparql Secrets In Jena-Fuseki - DataScienceCentral.com
24 July 2022, Data Science Central

Extract and query knowledge graphs using Apache Jena (SPARQL Engine)
4 December 2019, Towards Data Science

6 Libraries in Java for Machine Learning
2 October 2023, Analytics India Magazine

A catalogue with semantic annotations makes multilabel datasets FAIR | Scientific Reports
4 May 2022, Nature.com

MarkLogic Hones Its Triple Store
18 August 2015, Datanami

provided by Google News

etcd: the Not-so-Secret Sauce in Google's Kubernetes and Pivotal's Cloud Foundry
31 May 2024, Data Center Knowledge

Monitor Amazon EKS Control Plane metrics using AWS Open Source monitoring services | Amazon Web Services
12 October 2023, AWS Blog

6 Cool Kubernetes Operators and How to Use Them
22 January 2024, hackernoon.com

Killing a market, softly: How an RBI communique could end India's thriving ETCD market
7 April 2024, The Economic Times

RBI reiterates need for underlying forex exposure for rupee derivatives transactions | Stock Market News
5 April 2024, Mint

provided by Google News

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

provided by Google News

IBM Buys Informix for $1 Billion
1 June 2024, ITPro Today

IBM Informix: A key part of IBM’s hybrid cloud and AI strategy
11 January 2024, IBM

Unlock the value of your Informix data for advanced analytics and AI with watsonx.data
24 April 2024, IBM

IBM Informix review: What you need to know about the software
12 December 2022, TechRepublic

IBM Informix Database in the Cloud
1 May 2009, AWS Blog

provided by Google News

Share this page