DBMS > Ehcache vs. EventStoreDB vs. HEAVY.AI vs. Lovefield vs. TimesTen

System Properties Comparison Ehcache vs. EventStoreDB vs. HEAVY.AI vs. Lovefield vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Industrial-strength, open-source database solution built from the ground up for event sourcing.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Embeddable relational database for web apps written in pure JavaScript

In-Memory RDBMS compatible to Oracle

Primary database model

Key-value store

Event Store

Relational DBMS

Secondary database models

Spatial DBMS

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

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

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

www.ehcache.org

www.eventstore.com

github.com/heavyai/heavydb
www.heavy.ai

google.github.io/lovefield

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

www.ehcache.org/documentation

developers.eventstore.com

docs.heavy.ai

github.com/google/lovefield/blob/master/docs/spec_index.md

docs.oracle.com/database/timesten-18.1

Developer

Terracotta Inc, owned by Software AG

Event Store Limited

HEAVY.AI, Inc.

Google

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2009

2012

2016

2014

1998

Current release

3.10.0, March 2022

21.2, February 2021

5.10, January 2022

2.1.12, February 2017

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2; enterprise edition available

Open Source

Apache 2.0

commercial

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++ and CUDA

JavaScript

Server operating systems

All OS with a Java VM

Linux
Windows

Linux

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

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

yes

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

JCache

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

Java

All languages supporting JDBC/ODBC/Thrift
Python

JavaScript

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

PL/SQL

Triggers

yes

Cache Event Listeners

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

Round robin

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

Multi-source replication

none

Multi-source replication
Source-replica replication

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)

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

using MemoryDB

yes

User concepts

Access control

fine grained access rights according to SQL-standard

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