DBMS > atoti vs. Kyligence Enterprise vs. Microsoft Azure SQL Database vs. Prometheus vs. SQLite

System Properties Comparison atoti vs. Kyligence Enterprise vs. Microsoft Azure SQL Database vs. Prometheus vs. SQLite

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

A distributed analytics engine for big data, built on top of Apache Kylin

Database as a Service offering with high compatibility to Microsoft SQL Server

Open-source Time Series DBMS and monitoring system

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	0.40
Rank	#269	Overall
	#124	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

atoti.io

kyligence.io/kyligence-enterprise

azure.microsoft.com/en-us/products/azure-sql/database

prometheus.io

www.sqlite.org

Technical documentation

docs.atoti.io

docs.microsoft.com/en-us/azure/azure-sql

prometheus.io/docs

www.sqlite.org/docs.html

Developer

ActiveViam

Kyligence, Inc.

Microsoft

Dwayne Richard Hipp

Initial release

2016

2010

2015

2000

Current release

V12

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

free versions available

commercial

Open Source

Apache 2.0

Open Source

Public Domain

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++

Server operating systems

Linux

hosted

Linux
Windows

server-less

Data scheme

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Numeric data only

yes

not rigid because of 'dynamic typing' concept.

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

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

ANSI SQL for queries (using Apache Calcite)

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

RESTful HTTP/JSON API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

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

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

Python

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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, multi-version concurrency control (MVCC)

yes

via file-system locks

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

fine grained access rights according to SQL-standard

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