DBMS > OpenMLDB vs. RavenDB vs. Sphinx

System Properties Comparison OpenMLDB vs. RavenDB vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Primary database model

Time Series DBMS

Document store

Search engine

Secondary database models

Relational DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.11
Rank	#339	Overall
	#30	Time Series DBMS

Score	2.68
Rank	#102	Overall
	#19	Document stores

Score	5.97
Rank	#56	Overall
	#5	Search engines

Website

openmldb.ai

ravendb.net

sphinxsearch.com

Technical documentation

openmldb.ai/docs/zh/main

ravendb.net/docs

sphinxsearch.com/docs

Developer

4 Paradigm Inc.

Hibernating Rhinos

Sphinx Technologies Inc.

Initial release

2020

2010

2001

Current release

2024-2 February 2024

5.4, July 2022

3.5.1, February 2023

License

Commercial or Open Source

Open Source

AGPL version 3, commercial license available

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

C++, Java, Scala

C++

Server operating systems

Linux

Linux
macOS
Raspberry Pi
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

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 (RQL)

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
SQLAlchemy

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Proprietary protocol

Supported programming languages

C++
Go
Java
Python
Scala

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

Transaction concepts

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

ACID, Cluster-wide transaction available

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

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

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More resources

DB-Engines blog posts

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