DBMS > Bangdb vs. GeoSpock vs. Hawkular Metrics vs. KairosDB vs. ToroDB

System Properties Comparison Bangdb vs. GeoSpock vs. Hawkular Metrics vs. KairosDB vs. ToroDB

Editorial information provided by DB-Engines

Name

GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.

ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

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

Spatial and temporal data processing engine for extreme data scale

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

Distributed Time Series DBMS based on Cassandra or H2

A MongoDB-compatible JSON document store, built on top of PostgreSQL

Primary database model

Document store
Graph DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

Document store

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Website

bangdb.com

geospock.com

www.hawkular.org

github.com/kairosdb/kairosdb

github.com/torodb/server

Technical documentation

docs.bangdb.com

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

kairosdb.github.io

Developer

Sachin Sinha, BangDB

GeoSpock

Community supported by Red Hat

8Kdata

Initial release

2012

2014

2013

2016

Current release

BangDB 2.0, October 2021

2.0, September 2019

1.2.2, November 2018

License

Commercial or Open Source

Open Source

BSD 3

commercial

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

AGPL-V3

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

C, C++

Java, Javascript

Java

Server operating systems

Linux

hosted

Linux
OS X
Windows

All OS with a Java 7 VM

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

yes

string, integer, double, boolean, date, object_id

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

temporal, categorical

SQL

Support of SQL

SQL like support with command line tool

ANSI SQL for query only (using Presto)

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC

HTTP REST

Graphite protocol
HTTP REST
Telnet API

Supported programming languages

C
C#
C++
Java
Python

Go
Java
Python
Ruby

Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Triggers

yes, Notifications (with Streaming only)

yes

via Hawkular Alerting

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

Automatic sharding

Sharding

based on Cassandra

Sharding

based on Cassandra

Sharding

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

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

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)

Access rights for users can be defined per table

simple password-based access control

Access rights for users and roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

How GeoSpock is supercharging geospatial analytics
23 February 2021, ComputerWeekly.com

Imagining an 'Everything Connected' World With Geospock | AWS Startups Blog
20 June 2019, AWS Blog

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, VanillaPlus

nChain Leads Investment Round in Extreme-scale Data Firm GeoSpock
2 October 2020, AlexaBlockchain

Smart Cities, Autonomous Vehicles, Artificial General Intelligence Robotics: Q&A with Steve Marsh, GeoSpock
16 May 2018, ExchangeWire

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

Real-Time Performance and Health Monitoring Using Netdata
2 September 2019, CNX Software

Expo: Real Time A/B Testing and Monitoring with Spark Streaming and Kafka at Walmart Labs
24 May 2019, InfoQ.com

provided by Google News

Share this page