DBMS > Fauna vs. Oracle NoSQL vs. Splice Machine vs. SQLite vs. WakandaDB

System Properties Comparison Fauna vs. Oracle NoSQL vs. Splice Machine vs. SQLite vs. WakandaDB

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.

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Widely used embeddable, in-process RDBMS

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Document store
Key-value store
Relational DBMS

Relational DBMS

Object oriented DBMS

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

Score	1.55
Rank	#154	Overall
	#26	Document stores
	#14	Graph DBMS
	#72	Relational DBMS
	#13	Time Series DBMS

Score	2.96
Rank	#103	Overall
	#18	Document stores
	#17	Key-value stores
	#52	Relational DBMS

Score	0.54
Rank	#255	Overall
	#116	Relational DBMS

Score	116.01
Rank	#10	Overall
	#7	Relational DBMS

Score	0.09
Rank	#352	Overall
	#16	Object oriented DBMS

Website

fauna.com

www.oracle.com/database/nosql/technologies/nosql

splicemachine.com

www.sqlite.org

wakanda.github.io

Technical documentation

docs.fauna.com

docs.oracle.com/en/database/other-databases/nosql-database/index.html

splicemachine.com/how-it-works

www.sqlite.org/docs.html

wakanda.github.io/doc

Developer

Fauna, Inc.

Oracle

Splice Machine

Dwayne Richard Hipp

Wakanda SAS

Initial release

2014

2011

2014

2000

2012

Current release

23.3, December 2023

3.1, March 2021

3.45.3 (15 April 2024), April 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

AGPL 3.0, commercial license available

Open Source

Public Domain

Open Source

AGPLv3, extended commercial license available

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++, JavaScript

Server operating systems

hosted

Linux
Solaris SPARC/x86

Linux
OS X
Solaris
Windows

server-less

Linux
OS X
Windows

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

dynamic column types

yes

Typing

predefined data types such as float or date

optional

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

SQL-like DML and DDL statements

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

RESTful HTTP API

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

C
C#
Go
Java
JavaScript (Node.js)
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

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

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

via file-system locks

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

off heap cache

yes

User concepts

Access control

Identity management, authentication, and access control

Access rights for users and roles

Access rights for users, groups and roles according to SQL-standard

yes

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