DBMS > Alibaba Cloud Table Store vs. Citus vs. FatDB vs. Microsoft Azure Data Explorer vs. TempoIQ

System Properties Comparison Alibaba Cloud Table Store vs. Citus vs. FatDB vs. Microsoft Azure Data Explorer vs. TempoIQ

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

A fully managed Wide Column Store for large quantities of semi-structured data with real-time access

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Fully managed big data interactive analytics platform

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Primary database model

Wide column store

Relational DBMS

Document store
Key-value store

Relational DBMS

column oriented

Time Series 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	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	4.38
Rank	#77	Overall
	#41	Relational DBMS

Website

www.alibabacloud.com/product/table-store

www.citusdata.com

azure.microsoft.com/services/data-explorer

tempoiq.com (offline)

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.citusdata.com

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

Developer

Alibaba

FatCloud

Microsoft

TempoIQ

Initial release

2016

2010

2012

2019

2012

Current release

8.1, December 2018

cloud service with continuous releases

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also 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.

Implementation language

Server operating systems

hosted

Linux

Windows

hosted

Data scheme

schema-free

yes

schema-free

Fixed schema with schema-less datatypes (dynamic)

schema-free

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

specific XML type available, but no XML query functionality

yes

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

standard, with numerous extensions

Via inetgration in SQL Server

Kusto Query Language (KQL), SQL subset

APIs and other access methods

HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

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

HTTP API

Supported programming languages

Java
Python

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

C#
Java
JavaScript

Node.js
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

yes

via applications

Yes, possible languages: KQL, Python, R

Triggers

yes

via applications

yes

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

yes

Realtime Alerts

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Source-replica replication

other methods possible by using 3rd party extensions

selectable replication factor

yes

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

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row 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.

User concepts

Access control

Access rights based on subaccounts and tokens

fine grained access rights according to SQL-standard

Can implement custom security layer via applications

Azure Active Directory Authentication

simple authentication-based access control

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