DBMS > Faircom DB vs. KairosDB vs. SQLite vs. SurrealDB

System Properties Comparison Faircom DB vs. KairosDB vs. SQLite vs. SurrealDB

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Editorial information provided by DB-Engines

Name

Description

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Distributed Time Series DBMS based on Cassandra or H2

Widely used embeddable, in-process RDBMS

A fully ACID transactional, developer-friendly, multi-model DBMS

Primary database model

Key-value store
Relational DBMS

Time Series DBMS

Relational DBMS

Document store
Graph DBMS

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

Score	0.18
Rank	#314	Overall
	#45	Key-value stores
	#141	Relational DBMS

Score	0.60
Rank	#238	Overall
	#20	Time Series DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Score	1.11
Rank	#174	Overall
	#30	Document stores
	#17	Graph DBMS

Website

www.faircom.com/products/faircom-db

github.com/kairosdb/kairosdb

www.sqlite.org

surrealdb.com

Technical documentation

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

kairosdb.github.io

www.sqlite.org/docs.html

surrealdb.com/docs

Developer

FairCom Corporation

Dwayne Richard Hipp

SurrealDB Ltd

Initial release

1979

2013

2000

2022

Current release

V13, July 2024

1.2.2, November 2018

3.46.1 (13 August 2024), August 2024

v1.5.0, May 2024

License

Commercial or Open Source

commercial

Restricted, free version available

Open Source

Apache 2.0

Open Source

Public Domain

Open Source

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

ANSI C, C++

Java

Rust

Server operating systems

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux
OS X
Windows

server-less

Linux
macOS
Windows

Data scheme

schema free, schema optional, schema required, partial schema,

schema-free

yes

dynamic column types

schema-free

Typing

predefined data types such as float or date

yes, ANSI SQL Types, JSON, typed binary structures

yes

not rigid because of 'dynamic typing' concept.

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

SQL

Support of SQL

yes, ANSI SQL with proprietary extensions

yes

SQL-92 is not fully supported

SQL-like query language

APIs and other access methods

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

Graphite protocol
HTTP REST
Telnet API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

GraphQL
RESTful HTTP API
WebSocket

Supported programming languages

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Java
JavaScript

Node.js
PHP
Python

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

Deno
Go
JavaScript (Node.js)
Rust

Server-side scripts

Stored procedures

yes

.Net, JavaScript, C/C++

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Sharding

based on Cassandra

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

selectable replication factor

based on Cassandra

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

yes

Durability

Support for making data persistent

Yes, tunable from durable to delayed durability to in-memory

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 with additional protections for files

simple password-based access control

yes, based on authentication and database rules

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