DBMS > Fauna vs. HugeGraph vs. IBM Db2 Event Store

System Properties Comparison Fauna vs. HugeGraph vs. IBM Db2 Event Store

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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 fast-speed and highly-scalable Graph DBMS

Distributed Event Store optimized for Internet of Things use cases

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Graph DBMS

Event Store
Time Series 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	0.13
Rank	#336	Overall
	#32	Graph DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Website

fauna.com

github.com/hugegraph
hugegraph.apache.org

www.ibm.com/products/db2-event-store

Technical documentation

docs.fauna.com

hugegraph.apache.org/docs

www.ibm.com/docs/en/db2-event-store

Developer

Fauna, Inc.

Baidu

IBM

Initial release

2014

2018

2017

Current release

0.9

2.0

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

free developer edition 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 and C++

Server operating systems

hosted

Linux
macOS
Unix

Linux

Linux, macOS, Windows for the developer addition

Data scheme

schema-free

yes

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.

Secondary indexes

yes

also supports composite index and range index

SQL

Support of SQL

yes

through the embedded Spark runtime

APIs and other access methods

RESTful HTTP API

Java API
RESTful HTTP API
TinkerPop Gremlin

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Groovy
Java
Python

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

Server-side scripts

Stored procedures

user defined functions

asynchronous Gremlin script jobs

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

depending on used storage backend, e.g. Cassandra and HBase

Active-active shard replication

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

edges in graph

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

Users, roles and permissions

fine grained access rights according to SQL-standard

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More resources

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