DBMS > Fauna vs. Hawkular Metrics vs. SQream DB vs. STSdb

System Properties Comparison Fauna vs. Hawkular Metrics vs. SQream DB vs. STSdb

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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.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

a GPU-based, columnar RDBMS for big data analytics workloads

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Time Series DBMS

Relational DBMS

Key-value store

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	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.70
Rank	#227	Overall
	#104	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

fauna.com

www.hawkular.org

sqream.com

github.com/STSSoft/STSdb4

Technical documentation

docs.fauna.com

www.hawkular.org/hawkular-metrics/docs/user-guide

docs.sqream.com

Developer

Fauna, Inc.

Community supported by Red Hat

SQream Technologies

STS Soft SC

Initial release

2014

2017

2011

Current release

2022.1.6, December 2022

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

GPLv2, 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++, CUDA, Haskell, Java, Scala

Server operating systems

hosted

Linux
OS X
Windows

Linux

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

yes, ANSI Standard SQL Types

yes

primitive types and user defined types (classes)

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

yes

APIs and other access methods

RESTful HTTP API

HTTP REST

.Net
JDBC
ODBC

.NET Client API

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Go
Java
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

C#
Java

Server-side scripts

Stored procedures

user defined functions

user defined functions in Python

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

Sharding

based on Cassandra

horizontal and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

selectable replication factor

based on Cassandra

none

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.

User concepts

Access control

Identity management, authentication, and access control

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More resources

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