DBMS > BigObject vs. EsgynDB vs. Hawkular Metrics vs. OrigoDB

System Properties Comparison BigObject vs. EsgynDB vs. Hawkular Metrics vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

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

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

Technical documentation

docs.bigobject.io

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

origodb.com/docs

Developer

BigObject, Inc.

Esgyn

Community supported by Red Hat

Robert Friberg et al

Initial release

2015

2014

2009

under the name LiveDB

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

Apache 2.0

Open Source

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++, Java

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux

Linux
OS X
Windows

Linux
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

HTTP REST

.NET Client API
HTTP API
LINQ

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Go
Java
Python
Ruby

.Net

Server-side scripts

Stored procedures

Lua

Java Stored Procedures

yes

Triggers

yes

via Hawkular Alerting

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on Cassandra

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication between multi datacenters

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

Write ahead log

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Role based authorization

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