DBMS > Microsoft Azure Data Explorer vs. Oracle vs. RavenDB vs. Transbase vs. Vertica

System Properties Comparison Microsoft Azure Data Explorer vs. Oracle vs. RavenDB vs. Transbase vs. Vertica

Editorial information provided by DB-Engines

Name

Description

Fully managed big data interactive analytics platform

Widely used RDBMS

Open Source Operational and Transactional Enterprise NoSQL Document Database

A resource-optimized, high-performance, universally applicable RDBMS

Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.

Primary database model

column oriented

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

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

Graph DBMS
Spatial DBMS
Time Series DBMS

Spatial DBMS
Time Series DBMS

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

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Score	10.68
Rank	#43	Overall
	#27	Relational DBMS

Website

azure.microsoft.com/services/data-explorer

www.oracle.com/database

ravendb.net

www.transaction.de/en/products/transbase.html

www.vertica.com

Technical documentation

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

docs.oracle.com/en/database

ravendb.net/docs

www.transaction.de/en/products/transbase/features.html

vertica.com/documentation

Developer

Microsoft

Oracle

Hibernating Rhinos

Transaction Software GmbH

OpenText

previously Micro Focus and Hewlett Packard

Initial release

2019

1980

2010

1987

2005

Current release

cloud service with continuous releases

23c, September 2023

5.4, July 2022

Transbase 8.3, 2022

12.0.3, January 2023

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

AGPL version 3, commercial license available

commercial

free development license

commercial

Limited community edition free

Cloud-based only

Only available as a cloud service

yes

on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C and C++

C++

Server operating systems

hosted

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

Linux
macOS
Raspberry Pi
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Linux

Data scheme

Fixed schema with schema-less datatypes (dynamic)

yes

Schemaless in JSON and XML columns

schema-free

yes

Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.

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

all fields are automatically indexed

yes

No Indexes Required. Different internal optimization strategy, but same functionality included.

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

yes

with proprietary extensions

SQL-like query language (RQL)

yes

Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.

APIs and other access methods

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL

character-based, interactive, front-end utility

Supported programming languages

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

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

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

PL/SQL

also stored procedures in Java possible

yes

yes, PostgreSQL PL/pgSQL, with minor differences

Triggers

yes

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

yes

yes, called Custom Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

Sharding

horizontal partitioning, hierarchical 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.

Multi-source replication
Source-replica replication

Multi-source replication

Source-replica replication

Multi-source replication

One, or more copies of data replicated across nodes, or object-store used for repository.

MapReduce

Offers an API for user-defined Map/Reduce methods

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

can be realized in PL/SQL

yes

Bi-directional Spark integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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

ACID, Cluster-wide transaction available

yes

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.

yes

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

User concepts

Access control

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

More information provided by the system vendor

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