DBMS > Hawkular Metrics vs. LevelDB vs. Oracle NoSQL vs. XTDB

System Properties Comparison Hawkular Metrics vs. LevelDB vs. Oracle NoSQL vs. XTDB

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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.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

Primary database model

Time Series DBMS

Key-value store

Document store
Key-value store
Relational DBMS

Document store

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

Score	0.01
Rank	#377	Overall
	#39	Time Series DBMS

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	3.07
Rank	#86	Overall
	#15	Document stores
	#11	Key-value stores
	#47	Relational DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

www.hawkular.org

github.com/google/leveldb

www.oracle.com/database/nosql/technologies/nosql

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

Technical documentation

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

github.com/google/leveldb/blob/main/doc/index.md

docs.oracle.com/en/database/other-databases/nosql-database/index.html

www.xtdb.com/docs

Developer

Community supported by Red Hat

Google

Oracle

Juxt Ltd.

Initial release

2014

2011

2019

Current release

1.23, February 2021

24.1, May 2024

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

BSD

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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++

Java

Clojure

Server operating systems

Linux
OS X
Windows

Illumos
Linux
OS X
Windows

Linux
Solaris SPARC/x86

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

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

schema-free

Typing

predefined data types such as float or date

yes

optional

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 DML and DDL statements

limited SQL, making use of Apache Calcite

APIs and other access methods

HTTP REST

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

Go
Java
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

C
C#
Go
Java
JavaScript (Node.js)
Python

Clojure
Java

Server-side scripts

Stored procedures

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

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.

yes

off heap cache

User concepts

Access control

Access rights for users and roles

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