DBMS > Apache Jena - TDB vs. Databricks vs. EsgynDB vs. Snowflake

System Properties Comparison Apache Jena - TDB vs. Databricks vs. EsgynDB vs. Snowflake

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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

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

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

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

Primary database model

RDF store

Document store
Relational DBMS

Relational DBMS

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

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

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

www.databricks.com

www.esgyn.cn

www.snowflake.com

Technical documentation

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

docs.databricks.com

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

originally developed by HP Labs

Databricks

Esgyn

Snowflake Computing Inc.

Initial release

2000

2013

2015

2014

Current release

4.9.0, July 2023

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

commercial

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

Server operating systems

All OS with a Java VM

hosted

Linux

hosted

Data scheme

yes

RDF Schemas

Flexible Schema (defined schema, partial schema, schema free)

yes

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

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

with Databricks SQL

yes

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

Java

Python
R
Scala

All languages supporting JDBC/ODBC/ADO.Net

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

Java Stored Procedures

user defined functions

Triggers

yes

via event handler

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication between multi datacenters

yes

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

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

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

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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