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

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

Editorial information provided by DB-Engines

Name

Description

Distributed and scalable native Graph DBMS

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

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

Primary database model

Graph DBMS

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	1.45
Rank	#156	Overall
	#15	Graph DBMS

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

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

dgraph.io

fauna.com

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

splicemachine.com

wakanda.github.io

Technical documentation

dgraph.io/docs

docs.fauna.com

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

splicemachine.com/how-it-works

wakanda.github.io/doc

Developer

Dgraph Labs, Inc.

Fauna, Inc.

Oracle

Splice Machine

Wakanda SAS

Initial release

2016

2014

2011

2014

2012

Current release

23.3, December 2023

3.1, March 2021

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

Apache 2.0

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

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

Linux
OS X
Windows

hosted

Linux
Solaris SPARC/x86

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

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

yes

Typing

predefined data types such as float or date

yes

optional

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

APIs and other access methods

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

RESTful HTTP API

JDBC
Native Spark Datasource
ODBC

RESTful HTTP API

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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

JavaScript

Server-side scripts

Stored procedures

user defined functions

yes

Java

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

horizontal partitioning

consistent hashing

Sharding

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Synchronous replication via Raft

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

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

Planned for future releases

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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