DBMS > JaguarDB vs. MaxDB vs. Microsoft Azure Data Explorer vs. RocksDB

System Properties Comparison JaguarDB vs. MaxDB vs. Microsoft Azure Data Explorer vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Performant, highly scalable DBMS for AI and IoT applications

A robust and reliable RDBMS optimized to run all major SAP solutions

Fully managed big data interactive analytics platform

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Key-value store
Vector DBMS

Relational DBMS

column oriented

Key-value store

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	0.06
Rank	#381	Overall
	#59	Key-value stores
	#14	Vector DBMS

Score	2.26
Rank	#114	Overall
	#55	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.jaguardb.com

maxdb.sap.com

azure.microsoft.com/services/data-explorer

rocksdb.org

Technical documentation

www.jaguardb.com/support.html

maxdb.sap.com/documentation

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

github.com/facebook/rocksdb/wiki

Developer

DataJaguar, Inc.

SAP, acquired from Software AG (Adabas-D) in 1997

Microsoft

Facebook, Inc.

Initial release

2015

1984

2019

2013

Current release

3.3 July 2023

7.9.10.12, February 2024

cloud service with continuous releases

9.2.1, May 2024

License

Commercial or Open Source

Open Source

GPL V3.0

commercial

Limited community edition free

commercial

Open Source

BSD

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

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux

AIX
HP-UX
Linux
Solaris
Windows

hosted

Linux

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

schema-free

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

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

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

Kusto Query Language (KQL), SQL subset

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC
WebDAV

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

C++ API
Java API

Supported programming languages

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C#
Java
Perl
PHP
Python

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Yes, possible languages: KQL, Python, R

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

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

Eventual Consistency

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

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

rights management via user accounts

fine grained access rights according to SQL-standard

Azure Active Directory Authentication

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