DBMS > EXASOL vs. Microsoft Azure Data Explorer vs. OpenTSDB vs. Oracle

System Properties Comparison EXASOL vs. Microsoft Azure Data Explorer vs. OpenTSDB vs. Oracle

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Editorial information provided by DB-Engines

Name

Description

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

Fully managed big data interactive analytics platform

Scalable Time Series DBMS based on HBase

Widely used RDBMS

Primary database model

Relational DBMS

column oriented

Time Series DBMS

Relational DBMS

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

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	1244.08
Rank	#1	Overall
	#1	Relational DBMS

Website

www.exasol.com

azure.microsoft.com/services/data-explorer

opentsdb.net

www.oracle.com/database

Technical documentation

www.exasol.com/resources

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

opentsdb.net/docs/build/html/index.html

docs.oracle.com/en/database

Developer

Exasol

Microsoft

currently maintained by Yahoo and other contributors

Oracle

Initial release

2000

2019

2011

1980

Current release

cloud service with continuous releases

23c, September 2023

License

Commercial or Open Source

commercial

Open Source

LGPL

commercial

restricted free version is available

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 and C++

Server operating systems

hosted

Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

schema-free

yes

Schemaless in JSON and XML columns

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

numeric data for metrics, strings for tags

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

SQL

Support of SQL

yes

Kusto Query Language (KQL), SQL subset

yes

with proprietary extensions

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

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

HTTP API
Telnet API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java
Lua
Python
R

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

Erlang
Go
Java
Python
R
Ruby

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

user defined functions

Yes, possible languages: KQL, Python, R

PL/SQL

also stored procedures in Java possible

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on HBase

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

selectable replication factor

based on HBase

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

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

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

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

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

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