DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. BigObject vs. EJDB vs. eXtremeDB vs. Snowflake

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. BigObject vs. EJDB vs. eXtremeDB vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

Analytic DBMS for real-time computations and queries

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

Natively in-memory DBMS with options for persistency, high-availability and clustering

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Relational DBMS
Time Series DBMS

Relational DBMS

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

Score	0.79
Rank	#213	Overall
	#101	Relational DBMS

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	0.13
Rank	#331	Overall
	#46	Document stores

Score	0.79
Rank	#212	Overall
	#100	Relational DBMS
	#18	Time Series DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

bigobject.io

github.com/Softmotions/ejdb

www.mcobject.com

www.snowflake.com

Technical documentation

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

docs.bigobject.io

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

www.mcobject.com/docs/extremedb.htm

docs.snowflake.net/manuals/index.html

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

BigObject, Inc.

Softmotions

McObject

Snowflake Computing Inc.

Initial release

2016

2015

2012

2001

2014

Current release

8.2, 2021

License

Commercial or Open Source

commercial

free community edition available

Open Source

GPLv2

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 and C++

Server operating systems

hosted

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

server-less

AIX
HP-UX
Linux
macOS
Solaris
Windows

hosted

Data scheme

yes

schema-free

yes

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

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

support of XML interfaces available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

yes

with the option: eXtremeSQL

yes

APIs and other access methods

JDBC
ODBC

fluentd
ODBC
RESTful HTTP API

in-process shared library

.NET Client API
JDBC
JNI
ODBC
Proprietary protocol
RESTful HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C
Java
Perl
Python
R

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

.Net
C
C#
C++
Java
Lua
Python
Scala

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Lua

yes

user defined functions

Triggers

yes

by defining events

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

horizontal partitioning / sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

Active Replication Fabric™ for IoT
Multi-source replication

by means of eXtremeDB Cluster option
Source-replica replication

by means of eXtremeDB High Availability option

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

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

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Read/Write Locking

yes

Optimistic (MVCC) and pessimistic (locking) strategies available

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

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

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