DBMS > EsgynDB vs. HyperSQL vs. Sphinx vs. Warp 10

System Properties Comparison EsgynDB vs. HyperSQL vs. Sphinx vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Search engine

Time Series DBMS

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

Score	0.15
Rank	#325	Overall
	#144	Relational DBMS

Score	3.14
Rank	#85	Overall
	#46	Relational DBMS

Score	5.97
Rank	#56	Overall
	#5	Search engines

Score	0.06
Rank	#351	Overall
	#35	Time Series DBMS

Website

Technical documentation

hsqldb.org/web/hsqlDocsFrame.html

sphinxsearch.com/docs

www.warp10.io/content/02_Getting_started

Developer

Esgyn

Sphinx Technologies Inc.

SenX

Initial release

2015

2001

2015

Current release

2.7.2, June 2023

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

based on BSD license

Open Source

GPL version 2, commercial licence available

Open Source

Apache License 2.0

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

Java

C++

Java

Server operating systems

Linux

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

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 (SphinxQL)

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API

JDBC via HTTP
JDBC
ODBC

Proprietary protocol

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

All languages supporting JDBC/ODBC
Java

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

Java Stored Procedures

Java, SQL

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

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

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

none

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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.

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources

DB-Engines blog posts

The DB-Engines ranking includes now search engines
4 February 2013, Paul Andlinger

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