DBMS > Microsoft Azure Data Explorer vs. Newts vs. OrigoDB vs. SAP Advantage Database Server

System Properties Comparison Microsoft Azure Data Explorer vs. Newts vs. OrigoDB vs. SAP Advantage Database Server

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Editorial information provided by DB-Engines

Name

SAP Advantage Database Server seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

Fully managed big data interactive analytics platform

Time Series DBMS based on Cassandra

A fully ACID in-memory object graph database

Low-cost RDBMS with access to ISAM and FoxPro data structures

Primary database model

Relational DBMS

column oriented

Time Series DBMS

Document store
Object oriented 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

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

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

azure.microsoft.com/services/data-explorer

opennms.github.io/newts

origodb.com

www.sap.com/products/advantage-database-server.html

Technical documentation

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

github.com/OpenNMS/newts/wiki

origodb.com/docs

Developer

Microsoft

OpenNMS Group

Robert Friberg et al

Sybase, SAP

Initial release

2019

2014

2009

under the name LiveDB

1993

Current release

cloud service with continuous releases

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

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

hosted

Linux
OS X
Windows

Linux
Windows

Data scheme

Fixed schema with schema-less datatypes (dynamic)

schema-free

yes

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

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

all fields are automatically indexed

yes

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

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

HTTP REST
Java API

.NET Client API
HTTP API
LINQ

.NET Client API
ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

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

Java

.Net

Delphi
Perl
PHP

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

yes

Triggers

yes

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

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

based on Cassandra

horizontal partitioning

client side managed; servers are not synchronized

none

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 Cassandra

Source-replica replication

Multi-source replication

CONFLICT Trigger to resolve replication conflicts
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

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

caching of (temporary) tables can be configured

User concepts

Access control

Azure Active Directory Authentication

Role based authorization

fine grained access rights according to SQL-standard

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