DBMS > Drizzle vs. Fujitsu Enterprise Postgres vs. InfinityDB vs. STSdb vs. TerminusDB

System Properties Comparison Drizzle vs. Fujitsu Enterprise Postgres vs. InfinityDB vs. STSdb vs. TerminusDB

Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

A Java embedded Key-Value Store which extends the Java Map interface

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Relational DBMS

Key-value store

Graph DBMS

Secondary database models

Document store
Spatial DBMS

Document store
RDF store

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

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

www.postgresql.fastware.com

boilerbay.com

github.com/STSSoft/STSdb4

terminusdb.com

Technical documentation

www.postgresql.fastware.com/product-manuals

boilerbay.com/infinitydb/manual

terminusdb.github.io/terminusdb/#

Developer

Drizzle project, originally started by Brian Aker

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Boiler Bay Inc.

STS Soft SC

DataChemist Ltd.

Initial release

2008

2002

2011

2018

Current release

7.2.4, September 2012

Fujitsu Enterprise Postgres 14, January 2022

4.0

4.0.8, September 2015

11.0.0, January 2023

License

Commercial or Open Source

Open Source

GNU GPL

commercial

Open Source

GPLv2, commercial license available

Open Source

GPL V3

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

C++

Java

Prolog, Rust

Server operating systems

FreeBSD
Linux
OS X

Linux
Windows

All OS with a Java VM

Windows

Linux

Data scheme

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

yes

primitive types and user defined types (classes)

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.

Secondary indexes

yes

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

yes

with proprietary extensions

yes

SQL-like query language (WOQL)

APIs and other access methods

JDBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

.NET Client API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C
C++
Java
PHP

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Java

C#
Java

JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

partitioning by range, list and by hash

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

yes

Transaction concepts

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

ACID

Optimistic locking for transactions; no isolation for bulk loads

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory journaling

In-memory capabilities

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

User concepts

Access control

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

Role-based access control

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more

Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
» more

Licensing and pricing models

Core based licensing
» more

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