DBMS > Hawkular Metrics vs. Sadas Engine vs. StarRocks vs. Warp 10

System Properties Comparison Hawkular Metrics vs. Sadas Engine vs. StarRocks vs. Warp 10

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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.

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

An open source, high-performance columnar analytical database that enables real-time, multi-dimensional, and highly concurrent data analytics

Forked from Apache Doris

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#158	Relational DBMS

Score	1.04
Rank	#189	Overall
	#88	Relational DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

Technical documentation

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

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

docs.starrocks.io/en-us/latest/introduction/StarRocks_intro

www.warp10.io/content/02_Getting_started

Developer

Community supported by Red Hat

SADAS s.r.l.

The Linux Foundation

since Feb 2023

SenX

Initial release

2014

2006

2020

2015

Current release

8.0

2.5.3, March 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

free trial version available

Open Source

Apache Version 2.0

Open Source

Apache License 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

C++

C++, Java

Java

Server operating systems

Linux
OS X
Windows

AIX
Linux
Windows

Linux

Linux
OS X
Windows

Data scheme

schema-free

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

yes

APIs and other access methods

HTTP REST

JDBC
ODBC
Proprietary protocol

JDBC
MySQL protocol

HTTP API
Jupyter
WebSocket

Supported programming languages

Go
Java
Python
Ruby

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

Java

Server-side scripts

Stored procedures

user defined functions

yes

WarpScript

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

horizontal partitioning

horizontal partitioning (by range and hash)

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

selectable replication factor

based on HBase

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

based on HBase

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

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

Role based access control and fine grained access rights

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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