DBMS > Hawkular Metrics vs. HEAVY.AI vs. Hypertable vs. Kinetica vs. RocksDB

System Properties Comparison Hawkular Metrics vs. HEAVY.AI vs. Hypertable vs. Kinetica vs. RocksDB

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

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

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

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

Fully vectorized database across both GPUs and CPUs

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Secondary database models

Spatial DBMS

Spatial 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	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

www.hawkular.org

github.com/heavyai/heavydb
www.heavy.ai

www.kinetica.com

rocksdb.org

Technical documentation

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

docs.heavy.ai

docs.kinetica.com

github.com/facebook/rocksdb/wiki

Developer

Community supported by Red Hat

HEAVY.AI, Inc.

Hypertable Inc.

Kinetica

Facebook, Inc.

Initial release

2014

2016

2009

2012

2013

Current release

5.10, January 2022

0.9.8.11, March 2016

7.1, August 2021

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

GNU version 3. Commercial license available

commercial

Open Source

BSD

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++ and CUDA

C++

C, C++

C++

Server operating systems

Linux
OS X
Windows

Linux

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

schema-free

yes

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

JDBC
ODBC
Thrift
Vega

C++ API
Thrift

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

Go
Java
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

C++
Java
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

Triggers

yes

via Hawkular Alerting

yes

triggers when inserted values for one or more columns fall within a specified range

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Round robin

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication

selectable replication factor on file system level

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

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

GPU vRAM or System RAM

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles on table level

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