DBMS > Hawkular Metrics vs. HyperSQL vs. LMDB vs. Snowflake

System Properties Comparison Hawkular Metrics vs. HyperSQL vs. LMDB vs. Snowflake

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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.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

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

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

www.hawkular.org

hsqldb.org

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

www.snowflake.com

Technical documentation

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

hsqldb.org/web/hsqlDocsFrame.html

www.lmdb.tech/doc

docs.snowflake.net/manuals/index.html

Developer

Community supported by Red Hat

Symas

Snowflake Computing Inc.

Initial release

2014

2001

2011

2014

Current release

2.7.2, June 2023

0.9.32, January 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

based on BSD license

Open Source

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

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

Linux
Unix
Windows

hosted

Data scheme

schema-free

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

HTTP REST

HTTP API

JDBC via HTTP
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

Go
Java
Python
Ruby

All languages supporting JDBC/ODBC
Java

.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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Java, SQL

user defined functions

Triggers

yes

via Hawkular Alerting

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

User concepts

Access control

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles and pluggable authentication

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