DBMS > Elasticsearch vs. FoundationDB vs. Microsoft Access vs. RocksDB

System Properties Comparison Elasticsearch vs. FoundationDB vs. Microsoft Access vs. RocksDB

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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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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 distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

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.)

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Search engine

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Relational DBMS

Key-value store

Secondary database models

Document store
Spatial DBMS
Vector DBMS

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

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	1.06
Rank	#185	Overall
	#31	Document stores
	#28	Key-value stores
	#85	Relational DBMS

Score	101.16
Rank	#11	Overall
	#8	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

www.elastic.co/elasticsearch

github.com/apple/foundationdb

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

rocksdb.org

Technical documentation

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

apple.github.io/foundationdb

developer.microsoft.com/en-us/access

github.com/facebook/rocksdb/wiki

Developer

Elastic

FoundationDB

Microsoft

Facebook, Inc.

Initial release

2010

2013

1992

2013

Current release

8.6, January 2023

6.2.28, November 2020

1902 (16.0.11328.20222), March 2019

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Elastic License

Open Source

Apache 2.0

commercial

Bundled with Microsoft Office

Open Source

BSD

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++

Server operating systems

All OS with a Java VM

Linux
OS X
Windows

Windows

Not a real database server, but making use of DLLs

Linux

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

schema-free

some layers support schemas

yes

schema-free

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

All search fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

supported in specific SQL layer only

yes

but not compliant to any SQL standard

APIs and other access methods

Java API
RESTful HTTP/JSON API

ADO.NET
DAO
ODBC
OLE DB

C++ API
Java API

Supported programming languages

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

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

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

in SQL-layer only

yes

since Access 2010 using the ACE-engine

Triggers

yes

by using the 'percolation' feature

yes

since Access 2010 using the ACE-engine

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Linearizable consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

but no files for transaction logging

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

but no files for transaction logging

yes

In-memory capabilities

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

Memcached and Redis integration

yes

User concepts

Access control

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

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