DBMS > Amazon DocumentDB vs. FoundationDB vs. Google Cloud Bigtable vs. H2

System Properties Comparison Amazon DocumentDB vs. FoundationDB vs. Google Cloud Bigtable vs. H2

Please select another system to include it in the comparison.

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

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

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Key-value store
Wide column store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	1.03
Rank	#190	Overall
	#31	Document stores
	#28	Key-value stores
	#89	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Website

aws.amazon.com/documentdb

github.com/apple/foundationdb

cloud.google.com/bigtable

www.h2database.com

Technical documentation

aws.amazon.com/documentdb/resources

apple.github.io/foundationdb

cloud.google.com/bigtable/docs

www.h2database.com/html/main.html

Developer

FoundationDB

Google

Thomas Mueller

Initial release

2019

2013

2015

2005

Current release

6.2.28, November 2020

2.2.220, July 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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

C++

Java

Server operating systems

hosted

Linux
OS X
Windows

hosted

All OS with a Java VM

Data scheme

schema-free

some layers support schemas

schema-free

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

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C#
C++
Go
Java
JavaScript (Node.js)
Python

Java

Server-side scripts

Stored procedures

in SQL-layer only

Java Stored Procedures and User-Defined Functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

Internal replication in Colossus, and regional replication between two clusters in different zones

With clustering: 2 database servers on different computers operate on identical copies of a database

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

in SQL-layer only

yes

Transaction concepts

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

Atomic single-document operations

ACID

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

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

Access rights for users and roles

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

FoundationDB team's new venture, Antithesis, raises $47M to enhance software testing
13 February 2024, SiliconANGLE News

Stonebraker Seeks to Invert the Computing Paradigm with DBOS
12 March 2024, Datanami

Antithesis raises $47M to launch an automated testing platform for software
13 February 2024, TechCrunch

Deno adds scaleable messaging with new Queues feature, sparks debate about proprietary services • DEVCLASS
28 September 2023, DevClass

FoundationDB, a very interesting NoSQL database owned by Apple, is now an open-source project
19 April 2018, GeekWire

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google expands BigQuery with Gemini, brings vector support to cloud databases
29 February 2024, VentureBeat

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

provided by Google News

Share this page