DBMS > Brytlyt vs. Hawkular Metrics vs. Netezza vs. RocksDB

System Properties Comparison Brytlyt vs. Hawkular Metrics vs. Netezza vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

Data warehouse and analytics appliance part of IBM PureSystems

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

Primary database model

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

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

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

Website

brytlyt.io

www.hawkular.org

www.ibm.com/products/netezza

rocksdb.org

Technical documentation

docs.brytlyt.io

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

github.com/facebook/rocksdb/wiki

Developer

Brytlyt

Community supported by Red Hat

IBM

Facebook, Inc.

Initial release

2016

2014

2000

2013

Current release

5.0, August 2023

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

C, C++ and CUDA

Java

C++

Server operating systems

Linux
OS X
Windows

Linux

included in appliance

Linux

Data scheme

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

HTTP REST

JDBC
ODBC
OLE DB

C++ API
Java API

Supported programming languages

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

Go
Java
Python
Ruby

C
C++
Fortran
Java
Lua
Perl
Python
R

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in PL/pgSQL

yes

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

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

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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