DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. Brytlyt vs. EJDB vs. H2 vs. Microsoft Azure Cosmos DB

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. Brytlyt vs. EJDB vs. H2 vs. Microsoft Azure Cosmos DB

Editorial information provided by DB-Engines

Name

Description

An online MPP (Massively Parallel Processing) data warehousing service based on Greenplum

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Relational DBMS

Document store

Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

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

Score	0.76
Rank	#220	Overall
	#102	Relational DBMS

Score	0.38
Rank	#276	Overall
	#127	Relational DBMS

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	8.33
Rank	#46	Overall
	#30	Relational 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/hybriddb-postgresql

brytlyt.io

github.com/Softmotions/ejdb

www.h2database.com

azure.microsoft.com/services/cosmos-db

Technical documentation

www.alibabacloud.com/help/en/analyticdb-for-postgresql/latest/product-introduction-overview

docs.brytlyt.io

github.com/Softmotions/ejdb/blob/master/README.md

www.h2database.com/html/main.html

learn.microsoft.com/azure/cosmos-db

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Brytlyt

Softmotions

Thomas Mueller

Microsoft

Initial release

2016

2012

2005

2014

Current release

5.0, August 2023

2.2.220, July 2023

License

Commercial or Open Source

commercial

Open Source

GPLv2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++ and CUDA

Java

Server operating systems

hosted

Linux
OS X
Windows

server-less

All OS with a Java VM

hosted

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

JDBC
ODBC

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

in-process shared library

JDBC
ODBC

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

Supported programming languages

C
Java
Perl
Python
R

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

Java

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

Server-side scripts

Stored procedures

yes

user defined functions

in PL/pgSQL

Java Stored Procedures and User-Defined Functions

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

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

none

With clustering: 2 database servers on different computers operate on identical copies of a database

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

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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