DBMS > Fauna vs. IBM Db2 Event Store vs. Realm vs. Riak TS vs. Sequoiadb

System Properties Comparison Fauna vs. IBM Db2 Event Store vs. Realm vs. Riak TS vs. Sequoiadb

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 Event Store optimized for Internet of Things use cases

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

NewSQL database with distributed OLTP and SQL

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Event Store
Time Series DBMS

Document store

Time Series DBMS

Document store
Relational DBMS

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

Score	1.43
Rank	#148	Overall
	#26	Document stores
	#13	Graph DBMS
	#68	Relational DBMS
	#13	Time Series DBMS

Score	0.18
Rank	#312	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	7.05
Rank	#49	Overall
	#8	Document stores

Score	0.16
Rank	#321	Overall
	#27	Time Series DBMS

Score	0.39
Rank	#267	Overall
	#42	Document stores
	#125	Relational DBMS

Website

fauna.com

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

realm.io

www.sequoiadb.com

Technical documentation

docs.fauna.com

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

realm.io/docs

www.tiot.jp/riak-docs/riak/ts/latest

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Fauna, Inc.

IBM

Realm, acquired by MongoDB in May 2019

Open Source, formerly Basho Technologies

Sequoiadb Ltd.

Initial release

2014

2017

2014

2015

2013

Current release

2.0

3.0.0, September 2022

License

Commercial or Open Source

commercial

free developer edition available

Open Source

Server: AGPL; Client: Apache V2

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

C and C++

Erlang

C++

Server operating systems

hosted

Linux

Linux, macOS, Windows for the developer addition

Android
Backend: server-less
iOS
Windows

Linux
OS X

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

restricted

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes, limited

SQL-like query language

APIs and other access methods

RESTful HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

HTTP API
Native Erlang Interface

proprietary protocol using JSON

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

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

.Net
Java

with Android only
Objective-C
React Native
Swift

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

runs within the applications so server-side scripts are unnecessary

Erlang

JavaScript

Triggers

yes

Change Listeners

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Active-active shard replication

none

selectable replication factor

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

ACID

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

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

yes

In-memory capabilities

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

yes

In-Memory realm

User concepts

Access control

Identity management, authentication, and access control

fine grained access rights according to SQL-standard

yes

simple password-based access control

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