DBMS > Ehcache vs. gStore vs. Hawkular Metrics vs. TimescaleDB vs. YottaDB

System Properties Comparison Ehcache vs. gStore vs. Hawkular Metrics vs. TimescaleDB vs. YottaDB

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

A native Graph DBMS to store and maintain very large RDF datasets.

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

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

A fast and solid embedded Key-value store

Primary database model

Secondary database models

Relational DBMS

using the Octo plugin

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

Score	4.89
Rank	#67	Overall
	#8	Key-value stores

Score	0.04
Rank	#359	Overall
	#37	Graph DBMS
	#18	RDF stores

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Score	0.20
Rank	#317	Overall
	#47	Key-value stores

Website

Technical documentation

www.ehcache.org/documentation

en.gstore.cn/#/enDocs

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

docs.timescale.com

yottadb.com/resources/documentation

Developer

Terracotta Inc, owned by Software AG

Community supported by Red Hat

Timescale

YottaDB, LLC

Initial release

2009

2016

2014

2017

2001

Current release

3.10.0, March 2022

1.2, November 2023

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

BSD

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

AGPL 3.0

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

Server operating systems

All OS with a Java VM

Linux

Linux
OS X
Windows

Docker
Linux

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

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

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

full PostgreSQL SQL syntax

by using the Octo plugin

APIs and other access methods

JCache

HTTP API
SPARQL 1.1

HTTP REST

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

PostgreSQL wire protocol

using the Octo plugin
Proprietary protocol

Supported programming languages

Java

C++
Java
JavaScript (Node.js)
PHP
Python

Go
Java
Python
Ruby

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

C
Go
JavaScript (Node.js)
Lua
M
Perl
Python
Rust

Server-side scripts

Stored procedures

yes

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

Cache Event Listeners

yes

via Hawkular Alerting

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

based on Cassandra

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

selectable replication factor

based on Cassandra

Source-replica replication with hot standby and reads on replicas

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

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

yes

supports JTA and can work as an XA resource

yes

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

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

Users, roles and permissions, Role-Based Access Control (RBAC) supported

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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