DBMS > Alibaba Cloud Table Store vs. Apache Druid vs. Citus vs. jBASE vs. Microsoft Azure Cosmos DB

System Properties Comparison Alibaba Cloud Table Store vs. Apache Druid vs. Citus vs. jBASE vs. Microsoft Azure Cosmos DB

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

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

A robust multi-value DBMS comprising development tools and middleware

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Wide column store

Relational DBMS
Time Series DBMS

Relational DBMS

Multivalue DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Document store

Spatial DBMS

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

Score	0.31
Rank	#297	Overall
	#11	Wide column stores

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

www.alibabacloud.com/product/table-store

druid.apache.org

www.citusdata.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

azure.microsoft.com/services/cosmos-db

Technical documentation

www.alibabacloud.com/help/en/tablestore

druid.apache.org/docs/latest/design

docs.citusdata.com

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

learn.microsoft.com/azure/cosmos-db

Developer

Alibaba

Apache Software Foundation and contributors

Rocket Software (formerly Zumasys)

Microsoft

Initial release

2016

2012

2010

1991

2014

Current release

29.0.1, April 2024

8.1, December 2018

5.7

License

Commercial or Open Source

commercial

Open Source

Apache license v2

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

Java

Server operating systems

hosted

Linux
OS X
Unix

Linux

AIX
Linux
Windows

hosted

Data scheme

schema-free

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

yes

JSON types

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 properties auto-indexed by default

SQL

Support of SQL

SQL for querying

yes

standard, with numerous extensions

Embedded SQL for jBASE in BASIC

SQL-like query language

APIs and other access methods

HTTP API

JDBC
RESTful HTTP/JSON API

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

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

Java
Python

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

.Net
Basic
Jabbascript
Java

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

user defined functions

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

yes

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

manual/auto, time-based

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes, via HDFS, S3 or other storage engines

Source-replica replication

other methods possible by using 3rd party extensions

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

Multi-item ACID transactions with snapshot isolation within a partition

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

User concepts

Access control

Access rights based on subaccounts and tokens

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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