DBMS > Apache Jena - TDB vs. InfluxDB vs. Microsoft Azure Data Explorer vs. MySQL vs. Teradata

System Properties Comparison Apache Jena - TDB vs. InfluxDB vs. Microsoft Azure Data Explorer vs. MySQL vs. Teradata

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

DBMS for storing time series, events and metrics

Fully managed big data interactive analytics platform

Widely used open source RDBMS

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

column oriented

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Spatial DBMS

with GEO package

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine

support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	25.83
Rank	#28	Overall
	#1	Time Series DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

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

www.influxdata.com/products/influxdb-overview

azure.microsoft.com/services/data-explorer

www.mysql.com

www.teradata.com

Technical documentation

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

docs.influxdata.com/influxdb

docs.microsoft.com/en-us/azure/data-explorer

dev.mysql.com/doc

docs.teradata.com

Developer

Apache Software Foundation

originally developed by HP Labs

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Teradata

Initial release

2000

2013

2019

1995

1984

Current release

4.9.0, July 2023

2.7.6, April 2024

cloud service with continuous releases

8.3.0, January 2024

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

Open Source

MIT-License; commercial enterprise version available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Java

C and C++

Server operating systems

All OS with a Java VM

Linux
OS X

through Homebrew

hosted

FreeBSD
Linux
OS X
Solaris
Windows

hosted
Linux

Data scheme

yes

RDF Schemas

schema-free

Fixed schema with schema-less datatypes (dynamic)

yes

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

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

all fields are automatically indexed

yes

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

SQL-like query language

Kusto Query Language (KQL), SQL subset

yes

with proprietary extensions

yes

SQL 2016 + extensions

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

HTTP API
JSON over UDP

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

Java

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

Yes, possible languages: KQL, Python, R

yes

proprietary syntax

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

via event handler

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

in enterprise version only

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

selectable replication factor

in enterprise version only

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Depending on used storage engine

yes

User concepts

Access control

Access control via Jena Security

simple rights management via user accounts

Azure Active Directory Authentication

Users with fine-grained authorization concept

no user groups or roles

fine grained access rights according to SQL-standard

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