DBMS > Ehcache vs. Hawkular Metrics vs. Hypertable vs. StarRocks

System Properties Comparison Ehcache vs. Hawkular Metrics vs. Hypertable vs. StarRocks

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Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

A widely adopted Java cache with tiered storage options

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

An open source BigTable implementation based on distributed file systems such as Hadoop

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

Forked from Apache Doris

Primary database model

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

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	0.95
Rank	#193	Overall
	#89	Relational DBMS

Website

www.ehcache.org

www.hawkular.org

www.starrocks.io

Technical documentation

www.ehcache.org/documentation

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

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

Developer

Terracotta Inc, owned by Software AG

Community supported by Red Hat

Hypertable Inc.

The Linux Foundation

since Feb 2023

Initial release

2009

2014

2009

2020

Current release

3.10.0, March 2022

0.9.8.11, March 2016

3.3, June 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Open Source

GNU version 3. Commercial license available

Open Source

Apache Version 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

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

schema-free

yes

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

APIs and other access methods

JCache

HTTP REST

C++ API
Thrift

JDBC
MySQL protocol

Supported programming languages

Java

Go
Java
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

Java

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

Cache Event Listeners

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

based on Cassandra

Sharding

horizontal partitioning (by range and hash)

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

selectable replication factor

based on Cassandra

selectable replication factor on file system level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

supports JTA and can work as an XA resource

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

In-memory capabilities

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

yes

User concepts

Access control

Role based access control and fine grained access rights

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