DBMS > Alibaba Cloud Table Store vs. Citus vs. Kinetica vs. Sadas Engine vs. Snowflake

System Properties Comparison Alibaba Cloud Table Store vs. Citus vs. Kinetica vs. Sadas Engine vs. Snowflake

Editorial information provided by DB-Engines

Name

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

Fully vectorized database across both GPUs and CPUs

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

Wide column store

Relational DBMS

Secondary database models

Document store

Spatial DBMS
Time Series DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

www.alibabacloud.com/product/table-store

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.citusdata.com

docs.kinetica.com

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.snowflake.net/manuals/index.html

Developer

Alibaba

Kinetica

SADAS s.r.l.

Snowflake Computing Inc.

Initial release

2016

2010

2012

2006

2014

Current release

8.1, December 2018

7.1, August 2021

8.0

License

Commercial or Open Source

commercial

Open Source

AGPL, commercial license also available

commercial

free trial version 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

C, C++

C++

Server operating systems

hosted

Linux

AIX
Linux
Windows

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

Typing

predefined data types such as float or date

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

SQL

Support of SQL

yes

standard, with numerous extensions

SQL-like DML and DDL statements

yes

APIs and other access methods

HTTP API

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

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Proprietary protocol

CLI Client
JDBC
ODBC

Supported programming languages

Java
Python

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

C++
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

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

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

horizontal partitioning

yes

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

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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.

yes

GPU vRAM or System RAM

yes

managed by 'Learn by Usage'

User concepts

Access control

Access rights based on subaccounts and tokens

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

Access rights for users, groups and roles according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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