DBMS > Apache Jena - TDB vs. EXASOL vs. Google Cloud Bigtable vs. Snowflake vs. TimescaleDB

System Properties Comparison Apache Jena - TDB vs. EXASOL vs. Google Cloud Bigtable vs. Snowflake vs. TimescaleDB

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Cloud-based data warehousing service for structured and semi-structured data

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

Primary database model

RDF store

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	3.62
Rank	#83	Overall
	#3	RDF stores

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

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

www.exasol.com

cloud.google.com/bigtable

www.snowflake.com

www.timescale.com

Technical documentation

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

www.exasol.com/resources

cloud.google.com/bigtable/docs

docs.snowflake.net/manuals/index.html

docs.timescale.com

Developer

Apache Software Foundation

originally developed by HP Labs

Exasol

Google

Snowflake Computing Inc.

Timescale

Initial release

2000

2015

2014

2017

Current release

4.9.0, July 2023

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

Server operating systems

All OS with a Java VM

hosted

Linux
OS X
Windows

Data scheme

yes

RDF Schemas

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

SQL

Support of SQL

yes

full PostgreSQL SQL syntax

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

.Net
JDBC
ODBC
WebSocket

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

CLI Client
JDBC
ODBC

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

Supported programming languages

Java

Java
Lua
Python
R

C#
C++
Go
Java
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

user defined functions

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

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Internal replication in Colossus, and regional replication between two clusters in different zones

yes

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

TDB Transactions

ACID

Atomic single-row operations

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.

yes

User concepts

Access control

Access control via Jena Security

Access rights for users, groups and roles according to SQL-standard

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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