DBMS > Apache Jena - TDB vs. Google BigQuery vs. MySQL vs. SingleStore vs. Transbase

System Properties Comparison Apache Jena - TDB vs. Google BigQuery vs. MySQL vs. SingleStore vs. Transbase

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

Large scale data warehouse service with append-only tables

Widely used open source RDBMS

MySQL wire-compliant distributed RDBMS that combines an in-memory row-oriented and a disc-based column-oriented storage with patented universal storage to handle transactional and analytical workloads in one single table type

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

RDF store

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Spatial DBMS
Time Series DBMS
Vector DBMS

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

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	5.60
Rank	#62	Overall
	#35	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

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

cloud.google.com/bigquery

www.mysql.com

www.singlestore.com

www.transaction.de/en/products/transbase.html

Technical documentation

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

cloud.google.com/bigquery/docs

dev.mysql.com/doc

docs.singlestore.com

www.transaction.de/en/products/transbase/features.html

Developer

Apache Software Foundation

originally developed by HP Labs

Google

Oracle

since 2010, originally MySQL AB, then Sun

SingleStore Inc.

Transaction Software GmbH

Initial release

2000

2010

1995

2013

1987

Current release

4.9.0, July 2023

8.4.0, April 2024

8.5, January 2024

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

commercial

free developer edition available

commercial

free development license

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C and C++

C++, Go

C and C++

Server operating systems

All OS with a Java VM

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

64 bit version required

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

yes

RDF Schemas

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

but no triggers and foreign keys

yes

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC
Proprietary native API

Cluster Management API

as HTTP Rest and CLI
HTTP API
JDBC
MongoDB API
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Java

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Bash
C
C#
Java
JavaScript (Node.js)
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

yes

proprietary syntax

yes

Triggers

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

hash partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

Source-replica replication

stores two copies of each physical data partition on two separate nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can define user-defined aggregate functions for map-reduce-style calculations

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

TDB Transactions

Since BigQuery is designed for querying data

ACID

not for MyISAM storage engine

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

All updates are persistent, including those to disk-based columnstores and memory-based row stores. Transaction commits are supported via write-ahead log.

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

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Users with fine-grained authorization concept

no user groups or roles

Fine grained access control via users, groups and roles

fine grained access rights according to SQL-standard

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Licensing and pricing models

F ree Tier and Enterprise Edition
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