DBMS > Firebolt vs. Graphite vs. Sphinx vs. SQLite

System Properties Comparison Firebolt vs. Graphite vs. Sphinx vs. SQLite

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Editorial information provided by DB-Engines

Name

Description

Highly scalable cloud data warehouse and analytics product

Forked from Clickhouse

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

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

Widely used embeddable, in-process RDBMS

Primary database model

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

Score	1.73
Rank	#140	Overall
	#63	Relational DBMS

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

www.firebolt.io

github.com/graphite-project/graphite-web

sphinxsearch.com

www.sqlite.org

Technical documentation

docs.firebolt.io

graphite.readthedocs.io

sphinxsearch.com/docs

www.sqlite.org/docs.html

Developer

Firebolt Analytics Inc.

Chris Davis

Sphinx Technologies Inc.

Dwayne Richard Hipp

Initial release

2020

2006

2001

2000

Current release

3.5.1, February 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

GPL version 2, commercial licence available

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Python

C++

Server operating systems

hosted

Linux
Unix

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

server-less

Data scheme

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Numeric data only

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

yes

SQL-like query language (SphinxQL)

yes

SQL-92 is not fully supported

APIs and other access methods

.Net
ODBC
RESTful HTTP API

HTTP API
Sockets

Proprietary protocol

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Go
JavaScript (Node.js)
Python

JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

none

Replication methods

Methods for redundantly storing data on multiple nodes

depending on storage layer

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

locking

yes

via file-system locks

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

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