DBMS > Hawkular Metrics vs. PostGIS vs. RavenDB vs. Sequoiadb vs. Vitess

System Properties Comparison Hawkular Metrics vs. PostGIS vs. RavenDB vs. Sequoiadb vs. Vitess

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.

Spatial extension of PostgreSQL

Open Source Operational and Transactional Enterprise NoSQL Document Database

NewSQL database with distributed OLTP and SQL

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Time Series DBMS

Spatial DBMS

Document store

Document store
Relational DBMS

Relational DBMS

Secondary database models

Relational DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

Document store
Spatial DBMS

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

Technical documentation

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

postgis.net/documentation

ravendb.net/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

vitess.io/docs

Developer

Community supported by Red Hat

Hibernating Rhinos

Sequoiadb Ltd.

The Linux Foundation, PlanetScale

Initial release

2014

2005

2010

2013

Current release

3.4.2, February 2024

5.4, July 2022

15.0.2, December 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

GPL v2.0

Open Source

AGPL version 3, commercial license available

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache Version 2.0, commercial licenses available

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
macOS
Raspberry Pi
Windows

Linux

Docker
Linux
macOS

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL-like query language (RQL)

SQL-like query language

yes

with proprietary extensions

APIs and other access methods

HTTP REST

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

proprietary protocol using JSON

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Go
Java
Python
Ruby

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

.Net
C++
Java
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

yes

JavaScript

yes

proprietary syntax

Triggers

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

yes

based on PostgreSQL

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

based on PostgreSQL

Multi-source replication

Source-replica replication

Multi-source 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

Immediate 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.

Eventual Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

Document is locked during a transaction

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

yes

based on PostgreSQL

Authorization levels configured per client per database

simple password-based access control

Users with fine-grained authorization concept

no user groups or roles

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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