DBMS > BigObject vs. Datomic vs. Hawkular Metrics

System Properties Comparison BigObject vs. Datomic vs. Hawkular Metrics

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Relational DBMS

Time Series DBMS

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

Score	0.13
Rank	#332	Overall
	#147	Relational DBMS

Score	1.50
Rank	#148	Overall
	#68	Relational DBMS

Score	0.01
Rank	#373	Overall
	#38	Time Series DBMS

Website

bigobject.io

www.datomic.com

www.hawkular.org

Technical documentation

docs.bigobject.io

docs.datomic.com

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

Developer

BigObject, Inc.

Cognitect

Community supported by Red Hat

Initial release

2015

2012

2014

Current release

1.0.7180, July 2024

License

Commercial or Open Source

commercial

free community edition available

commercial

limited edition free

Open Source

Apache 2.0

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, Clojure

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)

All OS with a Java VM

Linux
OS X
Windows

Data scheme

yes

schema-free

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-like DML and DDL statements

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

RESTful HTTP API

HTTP REST

Supported programming languages

Clojure
Java

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

Lua

yes

Transaction Functions

Triggers

By using transaction functions

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

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

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

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

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