DBMS > Hawkular Metrics vs. JSqlDb vs. Microsoft Azure Table Storage vs. OrientDB vs. XTDB

System Properties Comparison Hawkular Metrics vs. JSqlDb vs. Microsoft Azure Table Storage vs. OrientDB vs. XTDB

Editorial information provided by DB-Engines

Name

JSqlDB 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.

JavaScript Query Language Database, stores JavaScript objects and primitives

A Wide Column Store for rapid development using massive semi-structured datasets

Multi-model DBMS (Document, Graph, Key/Value)

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Time Series DBMS

Document store
Object oriented DBMS

Wide column store

Document store
Graph DBMS
Key-value store

Document store

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.hawkular.org

jsqldb.org (offline)

azure.microsoft.com/en-us/services/storage/tables

orientdb.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

www.orientdb.com/docs/last/index.html

www.xtdb.com/docs

Developer

Community supported by Red Hat

Konrad von Backstrom

Microsoft

OrientDB LTD; CallidusCloud; SAP

Juxt Ltd.

Initial release

2014

2018

2012

2010

2019

Current release

0.8, December 2018

3.2.29, March 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

commercial

Open Source

Apache version 2

Open Source

MIT License

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

Clojure

Server operating systems

Linux
OS X
Windows

Linux
macOS
Windows

hosted

All OS with a Java JDK (>= JDK 6)

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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, no joins

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP REST

RESTful HTTP API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

HTTP REST
JDBC

Supported programming languages

Go
Java
Python
Ruby

JavaScript

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

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

Clojure
Java

Server-side scripts

Stored procedures

functions in JavaScript

Java, Javascript

Triggers

yes

via Hawkular Alerting

Hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

Multi-source replication

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

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

relationship in graphs

Transaction concepts

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

optimistic locking

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using RocksDB

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

Access rights based on private key authentication or shared access signatures

Access rights for users and roles; record level security configurable

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
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Graph DBMSs are gaining in popularity faster than any other database category
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