DBMS > Apache Jena - TDB vs. Cachelot.io vs. Drizzle vs. IBM Db2 Event Store vs. Microsoft SQL Server

System Properties Comparison Apache Jena - TDB vs. Cachelot.io vs. Drizzle vs. IBM Db2 Event Store vs. Microsoft SQL Server

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

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

In-memory caching system

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

Distributed Event Store optimized for Internet of Things use cases

Microsofts flagship relational DBMS

Primary database model

RDF store

Key-value store

Relational DBMS

Event Store
Time Series DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Website

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

cachelot.io

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

www.microsoft.com/en-us/sql-server

Technical documentation

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

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

learn.microsoft.com/en-US/sql/sql-server

Developer

Apache Software Foundation

originally developed by HP Labs

Drizzle project, originally started by Brian Aker

IBM

Microsoft

Initial release

2000

2015

2008

2017

1989

Current release

4.9.0, July 2023

7.2.4, September 2012

2.0

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

Open Source

Simplified BSD License

Open Source

GNU GPL

commercial

free developer edition available

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

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Implementation language

Java

C++

C and C++

C++

Server operating systems

All OS with a Java VM

FreeBSD
Linux
OS X

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

Data scheme

yes

RDF Schemas

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

yes

with proprietary extensions

yes

through the embedded Spark runtime

yes

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

Memcached protocol

JDBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

Java

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

C
C++
Java
PHP

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

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

Server-side scripts

Stored procedures

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

via event handler

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Active-active shard replication

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

TDB Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

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

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

fine grained access rights according to SQL-standard

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