DBMS > Apache Jena - TDB vs. EsgynDB vs. GeoSpock vs. Google BigQuery vs. TimescaleDB

System Properties Comparison Apache Jena - TDB vs. EsgynDB vs. GeoSpock vs. Google BigQuery vs. TimescaleDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Spatial and temporal data processing engine for extreme data scale

Large scale data warehouse service with append-only tables

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

RDF store

Relational DBMS

Time Series DBMS

Secondary database models

Time Series DBMS

Relational DBMS

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

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

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

www.esgyn.cn

geospock.com

cloud.google.com/bigquery

www.timescale.com

Technical documentation

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

cloud.google.com/bigquery/docs

docs.timescale.com

Developer

Apache Software Foundation

originally developed by HP Labs

Esgyn

GeoSpock

Google

Timescale

Initial release

2000

2015

2010

2017

Current release

4.9.0, July 2023

2.0, September 2019

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

commercial

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

Java

C++, Java

Java, Javascript

Server operating systems

All OS with a Java VM

Linux

hosted

Linux
OS X
Windows

Data scheme

yes

RDF Schemas

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

temporal, categorical

yes

SQL

Support of SQL

yes

ANSI SQL for query only (using Presto)

yes

full PostgreSQL SQL syntax

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

ADO.NET
JDBC
ODBC

JDBC

RESTful HTTP/JSON API

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

Supported programming languages

Java

All languages supporting JDBC/ODBC/ADO.Net

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

Java Stored Procedures

user defined functions

in JavaScript

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

via event handler

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Automatic sharding

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

TDB Transactions

ACID

Since BigQuery is designed for querying 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.

User concepts

Access control

Access control via Jena Security

fine grained access rights according to SQL-standard

Access rights for users can be defined per table

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

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

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