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

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

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

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

Widely used embeddable, in-process RDBMS

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	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational 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

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

www.sqlite.org/docs.html

docs.timescale.com

yottadb.com/resources/documentation

Developer

Terracotta Inc, owned by Software AG

Community supported by Red Hat

Dwayne Richard Hipp

Timescale

YottaDB, LLC

Initial release

2009

2014

2000

2017

2001

Current release

3.10.0, March 2022

3.46.0 (23 May 2024), May 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

Open Source

Public Domain

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

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

server-less

Linux
OS X
Windows

Docker
Linux

Data scheme

schema-free

yes

dynamic column types

yes

schema-free

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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

SQL-92 is not fully supported

yes

full PostgreSQL SQL syntax

by using the Octo plugin

APIs and other access methods

JCache

HTTP REST

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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

Go
Java
Python
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.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

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

none

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

none

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

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

fine grained access rights according to SQL-standard

Users and groups based on OS-security mechanisms

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