DBMS > InfluxDB vs. Machbase Neo vs. Sphinx vs. SQLite vs. TerarkDB

System Properties Comparison InfluxDB vs. Machbase Neo vs. Sphinx vs. SQLite vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

DBMS for storing time series, events and metrics

TimeSeries DBMS for AIoT and BigData

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

Widely used embeddable, in-process RDBMS

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Secondary database models

Spatial DBMS

with GEO package

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

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

www.influxdata.com/products/influxdb-overview

machbase.com

sphinxsearch.com

www.sqlite.org

github.com/bytedance/terarkdb

Technical documentation

docs.influxdata.com/influxdb

machbase.com/dbms

sphinxsearch.com/docs

www.sqlite.org/docs.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Machbase

Sphinx Technologies Inc.

Dwayne Richard Hipp

ByteDance, originally Terark

Initial release

2013

2001

2000

2016

Current release

2.7.6, April 2024

V8.0, August 2023

3.5.1, February 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

MIT-License; commercial enterprise version available

commercial

free test version available

Open Source

GPL version 2, commercial licence available

Open Source

Public Domain

commercial

restricted open source version 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++

Server operating systems

Linux
OS X

through Homebrew

Linux
macOS
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

server-less

Data scheme

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

Numeric data and Strings

yes

not rigid because of 'dynamic typing' concept.

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

yes

SQL

Support of SQL

SQL-like query language

SQL-like query language (SphinxQL)

yes

SQL-92 is not fully supported

APIs and other access methods

HTTP API
JSON over UDP

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

Proprietary protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

C++ API
Java API

Supported programming languages

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

C++
Java

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

in enterprise version only

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

in enterprise version only

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

via file-system locks

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

Depending on used storage engine

yes

volatile and lookup table

yes

User concepts

Access control

simple rights management via user accounts

simple password-based access control

More information provided by the system vendor

Specific characteristics

InfluxData is the creator of InfluxDB , the open source time series database. It...
» more

Competitive advantages

Time to Value InfluxDB is available in all the popular languages and frameworks,...
» more

Typical application scenarios

IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more

Key customers

InfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more

Market metrics

Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more

Licensing and pricing models

Open source core with closed source clustering available either on-premise or on...
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News

Scaling Data Collection: Solving Renewable Energy Challenges with InfluxDB
6 June 2024

Deadman Alerts with Grafana and InfluxDB Cloud 3.0
5 June 2024

Chasing the Skies: Monitoring Flights with InfluxDB
4 June 2024

Monitoring Your Cloud Environments and Applications with InfluxDB
30 May 2024

Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS
29 May 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.