DBMS > Ehcache vs. FoundationDB vs. Google BigQuery vs. Microsoft Access

System Properties Comparison Ehcache vs. FoundationDB vs. Google BigQuery vs. Microsoft Access

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Editorial information provided by DB-Engines

Name

Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.

Description

A widely adopted Java cache with tiered storage options

Ordered key-value store. Core features are complimented by layers.

Large scale data warehouse service with append-only tables

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Primary database model

Key-value store

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

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

Score	4.79
Rank	#66	Overall
	#8	Key-value stores

Score	0.97
Rank	#191	Overall
	#32	Document stores
	#28	Key-value stores
	#87	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	93.76
Rank	#12	Overall
	#8	Relational DBMS

Website

www.ehcache.org

github.com/apple/foundationdb

cloud.google.com/bigquery

www.microsoft.com/en-us/microsoft-365/access

Technical documentation

www.ehcache.org/documentation

apple.github.io/foundationdb

cloud.google.com/bigquery/docs

developer.microsoft.com/en-us/access

Developer

Terracotta Inc, owned by Software AG

FoundationDB

Google

Microsoft

Initial release

2009

2013

2010

1992

Current release

3.10.0, March 2022

6.2.28, November 2020

1902 (16.0.11328.20222), March 2019

License

Commercial or Open Source

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

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

All OS with a Java VM

Linux
OS X
Windows

hosted

Windows

Not a real database server, but making use of DLLs

Data scheme

schema-free

some layers support schemas

yes

Typing

predefined data types such as float or date

yes

some layers support typing

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

supported in specific SQL layer only

yes

but not compliant to any SQL standard

APIs and other access methods

JCache

RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

Supported programming languages

Java

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

Server-side scripts

Stored procedures

in SQL-layer only

user defined functions

in JavaScript

yes

since Access 2010 using the ACE-engine

Triggers

yes

Cache Event Listeners

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

by using Terracotta Server

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

by using Terracotta Server

yes

none

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)

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

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

Since BigQuery is designed for querying data

ACID

but no files for transaction logging

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using a tiered cache-storage approach

yes

but no files for transaction logging

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

a simple user-level security was built in till version Access 2003

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