DBMS > Hawkular Metrics vs. Hyprcubd vs. KeyDB vs. Netezza

System Properties Comparison Hawkular Metrics vs. Hyprcubd vs. KeyDB vs. Netezza

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Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded 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.

Serverless Time Series DBMS

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Time Series DBMS

Key-value store

Relational DBMS

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	0.71
Rank	#226	Overall
	#33	Key-value stores

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

www.hawkular.org

hyprcubd.com (offline)

github.com/Snapchat/KeyDB
keydb.dev

www.ibm.com/products/netezza

Technical documentation

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

docs.keydb.dev

Developer

Community supported by Red Hat

Hyprcubd, Inc.

EQ Alpha Technology Ltd.

IBM

Initial release

2014

2019

2000

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

BSD-3

commercial

Cloud-based only

Only available as a cloud service

yes

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

hosted

Linux

included in appliance

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

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

by using the Redis Search module

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

HTTP REST

gRPC (https)

Proprietary protocol

RESP - REdis Serialization Protoco

JDBC
ODBC
OLE DB

Supported programming languages

Go
Java
Python
Ruby

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

Lua

yes

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication
Source-replica replication

Source-replica replication

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

Eventual Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

Foreign keys

Referential integrity

Transaction concepts

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

Optimistic locking, atomic execution of commands blocks and scripts

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

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

token access

simple password-based access control and ACL

Users with fine-grained authorization concept

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