DBMS > Hawkular Metrics vs. OrigoDB vs. Sadas Engine vs. TerarkDB

System Properties Comparison Hawkular Metrics vs. OrigoDB vs. Sadas Engine vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Time Series DBMS

Document store
Object oriented DBMS

Relational DBMS

Key-value store

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.08
Rank	#367	Overall
	#56	Key-value stores

Website

www.hawkular.org

origodb.com

www.sadasengine.com

github.com/bytedance/terarkdb

Technical documentation

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

origodb.com/docs

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Community supported by Red Hat

Robert Friberg et al

SADAS s.r.l.

ByteDance, originally Terark

Initial release

2014

2009

under the name LiveDB

2006

2016

Current release

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

free trial version available

commercial

restricted open source version 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

Java

C++

Server operating systems

Linux
OS X
Windows

Linux
Windows

AIX
Linux
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

.NET Client API
HTTP API
LINQ

JDBC
ODBC
Proprietary protocol

C++ API
Java API

Supported programming languages

Go
Java
Python
Ruby

.Net

.Net
C
C#
C++
Groovy
Java
PHP
Python

C++
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

depending on model

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

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

yes

managed by 'Learn by Usage'

yes

User concepts

Access control

Role based authorization

Access rights for users, groups and roles according to SQL-standard

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