DBMS > HBase vs. OpenMLDB vs. RocksDB vs. Sphinx

System Properties Comparison HBase vs. OpenMLDB vs. RocksDB vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

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

An open-source machine learning database that provides a feature platform for training and inference

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

Secondary database models

Relational DBMS

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

Score	27.97
Rank	#26	Overall
	#2	Wide column stores

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

Technical documentation

hbase.apache.org/book.html

openmldb.ai/docs/zh/main

github.com/facebook/rocksdb/wiki

sphinxsearch.com/docs

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

4 Paradigm Inc.

Facebook, Inc.

Sphinx Technologies Inc.

Initial release

2008

2020

2013

2001

Current release

2.3.4, January 2021

2024-2 February 2024

9.2.1, May 2024

3.5.1, February 2023

License

Commercial or Open Source

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

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, Java, Scala

C++

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

schema-free, schema definition possible

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

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.

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

Java API
RESTful HTTP API
Thrift

JDBC
SQLAlchemy

C++ API
Java API

Proprietary protocol

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

C++
Go
Java
Python
Scala

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

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

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 or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Single row ACID (across millions of columns)

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

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