DBMS > Atos Standard Common Repository vs. ClickHouse vs. Hypertable vs. Microsoft Azure Data Explorer vs. SAP SQL Anywhere

System Properties Comparison Atos Standard Common Repository vs. ClickHouse vs. Hypertable vs. Microsoft Azure Data Explorer vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

An open source BigTable implementation based on distributed file systems such as Hadoop

Fully managed big data interactive analytics platform

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Document store
Key-value store

column oriented

Secondary database models

Time Series DBMS

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	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

clickhouse.com

azure.microsoft.com/services/data-explorer

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

clickhouse.com/docs

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

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Atos Convergence Creators

Clickhouse Inc.

Hypertable Inc.

Microsoft

SAP

formerly Sybase

Initial release

2016

2009

2019

1992

Current release

1703

v24.4.1.2088-stable, May 2024

0.9.8.11, March 2016

cloud service with continuous releases

17, July 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

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.

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Implementation language

Java

C++

Server operating systems

Linux

FreeBSD
Linux
macOS

Linux
OS X
Windows

an inofficial Windows port is available

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

Fixed schema with schema-less datatypes (dynamic)

yes

Typing

predefined data types such as float or date

optional

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

restricted

only exact value or prefix value scans

all fields are automatically indexed

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

LDAP

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

C++ API
Thrift

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

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C++
Java
Perl
PHP
Python
Ruby

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

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Yes, possible languages: KQL, Python, R

yes, in C/C++, Java, .Net or Perl

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

key based and custom

Sharding

Implicit feature of the cloud service

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

selectable replication factor on file system level

yes

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

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

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

Atomic execution of specific operations

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

User concepts

Access control

LDAP bind authentication

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

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