DBMS > Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics vs. ObjectBox vs. OceanBase

System Properties Comparison Microsoft Azure Cosmos DB vs. Microsoft Azure Synapse Analytics vs. ObjectBox vs. OceanBase

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Editorial information provided by DB-Engines

Name

Description

Globally distributed, horizontally scalable, multi-model database service

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

A distributed, high available RDBMS compatible with Oracle and MySQL

Primary database model

Document store
Graph DBMS
Key-value store
Wide column store

Relational DBMS

Object oriented DBMS
Vector DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Time Series DBMS

Document store
Wide column store

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

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

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS
	#7	Vector DBMS

Score	1.57
Rank	#149	Overall
	#69	Relational DBMS

Website

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/services/synapse-analytics

github.com/objectbox
objectbox.io

en.oceanbase.com

Technical documentation

learn.microsoft.com/azure/cosmos-db

docs.microsoft.com/azure/synapse-analytics

docs.objectbox.io

en.oceanbase.com/docs/oceanbase-database

Developer

Microsoft

ObjectBox Limited

OceanBase

previously Alibaba and Ant Group

Initial release

2014

2016

2017

2010

Current release

4.0 (May 2024)

4.3.0, April 2024

License

Commercial or Open Source

commercial

Bindings are released under Apache 2.0

Apache License 2.0

Open Source

Commercial license available

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 and C++

C++

Server operating systems

hosted

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

yes, plus "flex" map-like 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

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

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

ADO.NET
JDBC
ODBC

Proprietary native API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

Supported programming languages

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

C#
Java
PHP

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

Server-side scripts

Stored procedures

JavaScript

Transact SQL

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

Triggers

JavaScript

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding, horizontal partitioning

none

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

Data sync between devices allowing occasional connected databases to work completely offline

Multi-source replication using Paxos

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

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

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 can be defined down to the item level

yes

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

More information provided by the system vendor

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