DBMS > Hawkular Metrics vs. LMDB vs. Netezza vs. Sadas Engine vs. SiriDB

System Properties Comparison Hawkular Metrics vs. LMDB vs. Netezza vs. Sadas Engine vs. SiriDB

Editorial information provided by DB-Engines

Name

Description

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

A high performant, light-weight, embedded key-value database library

Data warehouse and analytics appliance part of IBM PureSystems

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Open Source Time Series DBMS

Primary database model

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Website

www.hawkular.org

www.symas.com/symas-embedded-database-lmdb

www.ibm.com/products/netezza

www.sadasengine.com

siridb.com

Technical documentation

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

www.lmdb.tech/doc

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

docs.siridb.com

Developer

Community supported by Red Hat

Symas

IBM

SADAS s.r.l.

Cesbit

Initial release

2014

2011

2000

2006

2017

Current release

0.9.32, January 2024

8.0

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

free trial version available

Open Source

MIT License

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++

Server operating systems

Linux
OS X
Windows

Linux
Unix
Windows

Linux

included in appliance

AIX
Linux
Windows

Linux

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

Numeric data

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

yes

APIs and other access methods

HTTP REST

JDBC
ODBC
OLE DB

JDBC
ODBC
Proprietary protocol

HTTP API

Supported programming languages

Go
Java
Python
Ruby

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
C
C#
C++
Groovy
Java
PHP
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Source-replica replication

none

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

managed by 'Learn by Usage'

yes

User concepts

Access control

Users with fine-grained authorization concept

Access rights for users, groups and roles according to SQL-standard

simple rights management via user accounts

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