DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. EJDB vs. Hive vs. Lovefield vs. Riak TS

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. EJDB vs. Hive vs. Lovefield vs. Riak TS

Editorial information provided by DB-Engines

Name

Description

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

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Embeddable relational database for web apps written in pure JavaScript

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Primary database model

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

Score	0.68
Rank	#231	Overall
	#105	Relational DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	0.20
Rank	#319	Overall
	#27	Time Series DBMS

Website

www.alibabacloud.com/product/hybriddb-postgresql

github.com/Softmotions/ejdb

hive.apache.org

google.github.io/lovefield

Technical documentation

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

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

cwiki.apache.org/confluence/display/Hive/Home

github.com/google/lovefield/blob/master/docs/spec_index.md

www.tiot.jp/riak-docs/riak/ts/latest

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Softmotions

Apache Software Foundation

initially developed by Facebook

Google

Open Source, formerly Basho Technologies

Initial release

2016

2012

2014

2015

Current release

3.1.3, April 2022

2.1.12, February 2017

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

GPLv2

Open Source

Apache Version 2

Open Source

Apache 2.0

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

Erlang

Server operating systems

hosted

server-less

All OS with a Java VM

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

Linux
OS X

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

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

restricted

SQL

Support of SQL

yes

SQL-like DML and DDL statements

SQL-like query language

via JavaScript builder pattern

yes, limited

APIs and other access methods

JDBC
ODBC

in-process shared library

JDBC
ODBC
Thrift

HTTP API
Native Erlang Interface

Supported programming languages

C
Java
Perl
Python
R

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

C++
Java
PHP
Python

JavaScript

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

Erlang

Triggers

yes

Using read-only observers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

none

selectable replication factor

none

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

typically not needed, however similar functionality with collection joins possible

yes

links between datasets can be stored

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

using MemoryDB

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

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