DBMS > Bangdb vs. Hawkular Metrics vs. RavenDB vs. STSdb

System Properties Comparison Bangdb vs. Hawkular Metrics vs. RavenDB vs. STSdb

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Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store
Graph DBMS
Time Series DBMS

Time Series DBMS

Document store

Key-value store

Secondary database models

Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	0.07
Rank	#346	Overall
	#47	Document stores
	#35	Graph DBMS
	#32	Time Series DBMS

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	2.68
Rank	#102	Overall
	#19	Document stores

Score	0.03
Rank	#365	Overall
	#54	Key-value stores

Website

bangdb.com

www.hawkular.org

ravendb.net

github.com/STSSoft/STSdb4

Technical documentation

docs.bangdb.com

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

ravendb.net/docs

Developer

Sachin Sinha, BangDB

Community supported by Red Hat

Hibernating Rhinos

STS Soft SC

Initial release

2012

2014

2010

2011

Current release

BangDB 2.0, October 2021

5.4, July 2022

4.0.8, September 2015

License

Commercial or Open Source

Open Source

BSD 3

Open Source

Apache 2.0

Open Source

AGPL version 3, commercial license available

Open Source

GPLv2, commercial license available

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

C, C++

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux
macOS
Raspberry Pi
Windows

Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like query language (RQL)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

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

.NET Client API

Supported programming languages

C
C#
C++
Java
Python

Go
Java
Python
Ruby

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

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

yes, Notifications (with Streaming only)

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

selectable replication factor

based on Cassandra

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

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.

Foreign keys

Referential integrity

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

User concepts

Access control

yes (enterprise version only)

Authorization levels configured per client per database

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