DBMS > Altibase vs. chDB vs. Microsoft Azure Data Explorer vs. TimesTen

System Properties Comparison Altibase vs. chDB vs. Microsoft Azure Data Explorer vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

An enterprise grade, high-performance RDBMS

An embedded SQL OLAP Engine powered by ClickHouse

Fully managed big data interactive analytics platform

An in-memory SQL relational database that delivers microsecond response and high throughput for OLTP applications. TimesTen can be deployed as a standalone database or as a cache to a backend Oracle database.

Primary database model

Relational DBMS

column oriented

Relational DBMS

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	0.87
Rank	#200	Overall
	#93	Relational DBMS

Score	0.05
Rank	#358	Overall
	#152	Relational DBMS

Score	3.28
Rank	#83	Overall
	#45	Relational DBMS

Score	1.26
Rank	#164	Overall
	#75	Relational DBMS

Website

altibase.com

github.com/chdb-io/chdb

azure.microsoft.com/services/data-explorer

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

doc.chdb.io

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

docs.oracle.com/en/database/other-databases/timesten/index.html

Developer

Altibase

Microsoft

Oracle

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

1999

2023

2019

1998

Current release

v7.3, 2023, August 2023

cloud service with continuous releases

Release 22.1

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

Open Source

Apache Version 2.0

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

C++

Server operating systems

AIX
HP-UX
Linux

server-less

hosted

IBM AIX Power PC 64-bit
Linux arm64
Linux x86-64
Solaris SPARC 64
Solaris SPARC/x86
Solaris x86-64

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

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

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

ANSI SQL-92

Close to ANSI SQL (SQL/JSON + extensions)

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

JDBC
ODBC
Proprietary protocol

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

ODBC
ODP.NET
Oracle Call Interface (OCI)
Pro*C/C++ programming interfaces
SQL and PL/SQL via JDBC

Supported programming languages

C
C++
Java

Bun
C
C++
Go
JavaScript (Node.js)
Python
Rust

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

C
C++
Java
Node.js
PL/SQL
Python

Server-side scripts

Stored procedures

stored procedures and stored functions

Yes, possible languages: KQL, Python, R

PL/SQL

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

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.

Multi-source replication
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

Immediate Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

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

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Azure Active Directory Authentication

fine grained access rights according to SQL-standard

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