DBMS > FeatureBase vs. Hawkular Metrics vs. RavenDB vs. TimesTen

System Properties Comparison FeatureBase vs. Hawkular Metrics vs. RavenDB vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.featurebase.com

www.hawkular.org

ravendb.net

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

docs.featurebase.com

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

ravendb.net/docs

docs.oracle.com/database/timesten-18.1

Developer

Molecula and Pilosa Open Source Contributors

Community supported by Red Hat

Hibernating Rhinos

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2017

2014

2010

1998

Current release

2022, May 2022

5.4, July 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

AGPL version 3, commercial license available

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux
macOS

Linux
OS X
Windows

Linux
macOS
Raspberry Pi
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

yes

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

SQL

Support of SQL

SQL queries

SQL-like query language (RQL)

yes

APIs and other access methods

gRPC
JDBC
Kafka Connector
ODBC

HTTP REST

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java
Python

Go
Java
Python
Ruby

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

PL/SQL

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

based on Cassandra

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes, using Linux fsync

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

Authorization levels configured per client per database

fine grained access rights according to SQL-standard

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