DBMS > Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Citus vs. Firebird vs. Kinetica

System Properties Comparison Alibaba Cloud Table Store vs. Amazon DynamoDB vs. Citus vs. Firebird vs. Kinetica

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

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

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

Firebird is an open source RDBMS forked from Borland's InterBase

Fully vectorized database across both GPUs and CPUs

Primary database model

Wide column store

Document store
Key-value 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	0.26
Rank	#301	Overall
	#12	Wide column stores

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Website

www.alibabacloud.com/product/table-store

aws.amazon.com/dynamodb

www.citusdata.com

www.firebirdsql.org

www.kinetica.com

Technical documentation

www.alibabacloud.com/help/en/tablestore

docs.aws.amazon.com/dynamodb

docs.citusdata.com

www.firebirdsql.org/en/reference-manuals

docs.kinetica.com

Developer

Alibaba

Amazon

Firebird Foundation

Kinetica

Initial release

2016

2012

2010

2000

As fork of Borland's InterBase

2012

Current release

8.1, December 2018

5.0.0, January 2024

7.1, August 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

AGPL, commercial license also available

Open Source

Initial Developer's Public License

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 and C++

C, C++

Server operating systems

hosted

Linux

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux

Data scheme

schema-free

yes

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

Secondary indexes

yes

SQL

Support of SQL

yes

standard, with numerous extensions

yes

SQL-like DML and DDL statements

APIs and other access methods

HTTP API

RESTful HTTP API

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

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

JDBC
ODBC
RESTful HTTP API

Supported programming languages

Java
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

C++
Java
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.

PSQL

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

Atomic single-row operations

ACID

ACID across one or more tables within a single AWS account and region

ACID

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

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

User concepts

Access control

Access rights based on subaccounts and tokens

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

Access rights for users and roles on table level

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