DBMS > Hawkular Metrics vs. Microsoft Azure Cosmos DB vs. Oracle Coherence vs. TimescaleDB vs. Transwarp Hippo

System Properties Comparison Hawkular Metrics vs. Microsoft Azure Cosmos DB vs. Oracle Coherence vs. TimescaleDB vs. Transwarp Hippo

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.

Globally distributed, horizontally scalable, multi-model database service

Oracles in-memory data grid solution

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Key-value store

Time Series DBMS

Vector DBMS

Secondary database models

Spatial DBMS

Relational DBMS

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

Score	0.08
Rank	#366	Overall
	#39	Time Series DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	1.97
Rank	#129	Overall
	#22	Key-value stores

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Score	0.05
Rank	#386	Overall
	#14	Vector DBMS

Website

www.hawkular.org

azure.microsoft.com/services/cosmos-db

www.oracle.com/java/coherence

www.timescale.com

www.transwarp.cn/en/subproduct/hippo

Technical documentation

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

learn.microsoft.com/azure/cosmos-db

docs.oracle.com/en/middleware/standalone/coherence

docs.timescale.com

Developer

Community supported by Red Hat

Microsoft

Oracle

Timescale

Initial release

2014

2007

2017

2023

Current release

14.1, August 2023

2.15.0, May 2024

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

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

C++

Server operating systems

Linux
OS X
Windows

hosted

All OS with a Java VM

Linux
OS X
Windows

Linux
macOS

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

JSON types

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

Vector, Numeric and String

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

All properties auto-indexed by default

yes

SQL

Support of SQL

SQL-like query language

yes

full PostgreSQL SQL syntax

APIs and other access methods

HTTP REST

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

JCache
JPA
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

RESTful HTTP API

Supported programming languages

Go
Java
Python
Ruby

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

.Net
C++
Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C++
Java
Python

Server-side scripts

Stored procedures

JavaScript

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

via Hawkular Alerting

JavaScript

yes

Live Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

Sharding

yes, across time and space (hash partitioning) attributes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

yes

Implicit feature of the cloud service

yes, with selectable consistency level

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

configurable

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

Access rights can be defined down to the item level

authentification to access the cache via certificates or http basic authentication

fine grained access rights according to SQL-standard

Role based access control and fine grained access rights

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