DBMS > Hawkular Metrics vs. Hyprcubd vs. RavenDB vs. Spark SQL vs. STSdb

System Properties Comparison Hawkular Metrics vs. Hyprcubd vs. RavenDB vs. Spark SQL vs. STSdb

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

Open Source Operational and Transactional Enterprise NoSQL Document Database

Spark SQL is a component on top of 'Spark Core' for structured data processing

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Secondary database models

Graph 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	2.92
Rank	#101	Overall
	#18	Document stores

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

www.hawkular.org

hyprcubd.com (offline)

ravendb.net

spark.apache.org/sql

github.com/STSSoft/STSdb4

Technical documentation

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

ravendb.net/docs

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Community supported by Red Hat

Hyprcubd, Inc.

Hibernating Rhinos

Apache Software Foundation

STS Soft SC

Initial release

2014

2010

2014

2011

Current release

5.4, July 2022

3.5.0 ( 2.13), September 2023

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

AGPL version 3, commercial license available

Open Source

Apache 2.0

Open Source

GPLv2, commercial license available

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

Scala

Server operating systems

Linux
OS X
Windows

hosted

Linux
macOS
Raspberry Pi
Windows

Linux
OS X
Windows

Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

primitive types and user defined types (classes)

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

SQL-like query language

SQL-like query language (RQL)

SQL-like DML and DDL statements

APIs and other access methods

HTTP REST

gRPC (https)

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

JDBC
ODBC

.NET Client API

Supported programming languages

Go
Java
Python
Ruby

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

Java
Python
R
Scala

C#
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

Multi-source replication

none

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

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

Transaction concepts

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

ACID, Cluster-wide transaction available

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.

User concepts

Access control

token access

Authorization levels configured per client per database

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