DBMS > Apache IoTDB vs. jBASE vs. Sphinx

System Properties Comparison Apache IoTDB vs. jBASE vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

A robust multi-value DBMS comprising development tools and middleware

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

Primary database model

Time Series DBMS

Multivalue DBMS

Search engine

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

Score	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Website

iotdb.apache.org

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

sphinxsearch.com

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

sphinxsearch.com/docs

Developer

Apache Software Foundation

Rocket Software (formerly Zumasys)

Sphinx Technologies Inc.

Initial release

2018

1991

2001

Current release

1.1.0, April 2023

5.7

3.5.1, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

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++

Server operating systems

All OS with a Java VM (>= 1.8)

AIX
Linux
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

optional

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

SQL-like query language

Embedded SQL for jBASE in BASIC

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
Native API

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Proprietary protocol

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

.Net
Basic
Jabbascript
Java

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 (by time range) + vertical partitioning (by deviceId)

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Foreign keys

Referential integrity

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.

In-memory capabilities

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

yes

User concepts

Access control

yes

Access rights can be defined down to the item level

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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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