DBMS > Apache Jena - TDB vs. etcd vs. Microsoft Azure Data Explorer vs. Snowflake

System Properties Comparison Apache Jena - TDB vs. etcd vs. Microsoft Azure Data Explorer 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

A distributed reliable key-value store

Fully managed big data interactive analytics platform

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

Primary database model

column oriented

Secondary database models

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

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

Score	3.75
Rank	#84	Overall
	#3	RDF stores

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

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

etcd.io
github.com/etcd-io/etcd

azure.microsoft.com/services/data-explorer

www.snowflake.com

Technical documentation

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

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

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

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

originally developed by HP Labs

Microsoft

Snowflake Computing Inc.

Initial release

2000

2019

2014

Current release

4.9.0, July 2023

3.4, August 2019

cloud service with continuous releases

License

Commercial or Open Source

Open Source

Apache License, Version 2.0

Open Source

Apache 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

Server operating systems

All OS with a Java VM

FreeBSD
Linux
Windows

experimental

hosted

Data scheme

yes

RDF Schemas

schema-free

Fixed schema with schema-less datatypes (dynamic)

yes

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

Typing

predefined data types such as float or date

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

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

gRPC
JSON over HTTP

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

CLI Client
JDBC
ODBC

Supported programming languages

Java

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

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Yes, possible languages: KQL, Python, R

user defined functions

Triggers

yes

via event handler

yes, watching key changes

yes

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

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes

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

yes

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

Immediate Consistency

Eventual Consistency
Immediate Consistency

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

Azure Active Directory Authentication

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

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