DBMS > Alibaba Cloud AnalyticDB for PostgreSQL vs. HBase vs. Realm vs. RocksDB vs. Sphinx

System Properties Comparison Alibaba Cloud AnalyticDB for PostgreSQL vs. HBase vs. Realm vs. RocksDB vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Open source search engine for searching in data from different sources, e.g. relational databases

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	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

www.alibabacloud.com/product/hybriddb-postgresql

Technical documentation

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

hbase.apache.org/book.html

realm.io/docs

github.com/facebook/rocksdb/wiki

sphinxsearch.com/docs

Developer

Alibaba / Pivotal Software Inc. / PostgreSQL Global Development Group

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Realm, acquired by MongoDB in May 2019

Facebook, Inc.

Sphinx Technologies Inc.

Initial release

2016

2008

2014

2013

2001

Current release

2.3.4, January 2021

8.11.4, April 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

BSD

Open Source

GPL version 2, commercial licence 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

Java

C++

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

Android
Backend: server-less
iOS
Windows

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free, schema definition possible

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
Thrift

C++ API
Java API

Proprietary protocol

Supported programming languages

C
Java
Perl
Python
R

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
Java

with Android only
Objective-C
React Native
Swift

C
C++
Go
Java
Perl
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Coprocessors in Java

runs within the applications so server-side scripts are unnecessary

Triggers

yes

Change Listeners

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

none

horizontal partitioning

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Multi-source replication
Source-replica replication

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

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

yes

In-Memory realm

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

yes

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