DBMS > Ehcache vs. EJDB vs. Google Cloud Datastore vs. Lovefield

System Properties Comparison Ehcache vs. EJDB vs. Google Cloud Datastore vs. Lovefield

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Editorial information provided by DB-Engines

Name

Description

A widely adopted Java cache with tiered storage options

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

Embeddable relational database for web apps written in pure JavaScript

Primary database model

Key-value store

Document store

Relational DBMS

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

Score	4.64
Rank	#68	Overall
	#8	Key-value stores

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	4.36
Rank	#72	Overall
	#12	Document stores

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Website

www.ehcache.org

github.com/Softmotions/ejdb

cloud.google.com/datastore

google.github.io/lovefield

Technical documentation

www.ehcache.org/documentation

github.com/Softmotions/ejdb/blob/master/README.md

cloud.google.com/datastore/docs

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

Developer

Terracotta Inc, owned by Software AG

Softmotions

Google

Initial release

2009

2012

2008

2014

Current release

3.10.0, March 2022

2.1.12, February 2017

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

GPLv2

commercial

Open Source

Apache 2.0

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

JavaScript

Server operating systems

All OS with a Java VM

server-less

hosted

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

tested with Chrome, Firefox, IE, Safari

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes, details here

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

SQL-like query language (GQL)

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JCache

in-process shared library

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Supported programming languages

Java

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

JavaScript

Server-side scripts

Stored procedures

using Google App Engine

Triggers

yes

Cache Event Listeners

Callbacks using the Google Apps Engine

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

none

Multi-source replication using Paxos

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable Consistency (Strong, Eventual, Weak)

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

via ReferenceProperties or Ancestor paths

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

Serializable Isolation within Transactions, Read Committed outside of Transactions

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

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

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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