DBMS > Fauna vs. KairosDB vs. Kingbase vs. Oracle Berkeley DB vs. Typesense

System Properties Comparison Fauna vs. KairosDB vs. Kingbase vs. Oracle Berkeley DB vs. Typesense

Editorial information provided by DB-Engines

Name

Description

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

Distributed Time Series DBMS based on Cassandra or H2

An enterprise-class RDBMS compatible with PostgreSQL and Oracle and widely used in China.

Widely used in-process key-value store

A typo-tolerant, in-memory search engine optimized for instant search-as-you-type experiences and developer productivity

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Search engine

Secondary database models

Document store
Spatial DBMS

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

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	0.45
Rank	#262	Overall
	#123	Relational DBMS

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	0.79
Rank	#210	Overall
	#14	Search engines

Website

fauna.com

github.com/kairosdb/kairosdb

www.kingbase.com.cn

www.oracle.com/database/technologies/related/berkeleydb.html

typesense.org

Technical documentation

docs.fauna.com

kairosdb.github.io

docs.oracle.com/cd/E17076_05/html/index.html

typesense.org/docs

Developer

Fauna, Inc.

BeiJing KINGBASE Information technologies inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2014

2013

1999

1994

2015

Current release

1.2.2, November 2018

V8.0, August 2021

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

commercial license available

Open Source

GPL V3

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

Scala

Java

C and Java

C, Java, C++ (depending on the Berkeley DB edition)

C++

Server operating systems

hosted

Linux
OS X
Windows

Linux
Windows

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

Data scheme

schema-free

yes

schema-free

pre-defined schema optional

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.

yes

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

yes

SQL interfaced based on SQLite is available

APIs and other access methods

RESTful HTTP API

Graphite protocol
HTTP REST
Telnet API

ADO.NET
gokb
JDBC
kdbndp
ODBC
PDI
PDO
Pro*C
psycopg2
QT

RESTful HTTP API

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Java
JavaScript

Node.js
PHP
Python

.Net
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

.Net

community maintained
Clojure

community maintained
Dart

community maintained
Go

community maintained
Java

community maintained
JavaScript
Perl

community maintained
PHP
Python
Ruby
Rust

community maintained
Swift

community maintained

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

based on Cassandra

horizontal partitioning (by range, list and hash) and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

based on Cassandra

yes

Source-replica replication

Multi-source replication using RAFT

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

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

In-memory capabilities

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

yes

User concepts

Access control

Identity management, authentication, and access control

simple password-based access control

fine grained access rights according to SQL-standard

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