DBMS > FoundationDB vs. Hazelcast vs. Microsoft SQL Server vs. XTDB

System Properties Comparison FoundationDB vs. Hazelcast vs. Microsoft SQL Server vs. XTDB

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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

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

A widely adopted in-memory data grid

Microsofts flagship relational DBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Key-value store

Relational DBMS

Document store

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Graph DBMS
Spatial DBMS

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

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

Score	5.97
Rank	#57	Overall
	#6	Key-value stores

Score	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

github.com/apple/foundationdb

hazelcast.com

www.microsoft.com/en-us/sql-server

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

apple.github.io/foundationdb

hazelcast.org/imdg/docs

learn.microsoft.com/en-US/sql/sql-server

www.xtdb.com/docs

Developer

FoundationDB

Hazelcast

Microsoft

Juxt Ltd.

Initial release

2013

2008

1989

2019

Current release

6.2.28, November 2020

5.3.6, November 2023

SQL Server 2022, November 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; commercial licenses available

commercial

restricted free version is available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

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Implementation language

C++

Java

C++

Clojure

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

some layers support schemas

schema-free

yes

schema-free

Typing

predefined data types such as float or date

some layers support typing

yes

yes, extensible-data-notation format

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.

yes

the object must implement a serialization strategy

yes

Secondary indexes

yes

SQL

Support of SQL

supported in specific SQL layer only

SQL-like query language

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JCache
JPA
Memcached protocol
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST
JDBC

Supported programming languages

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Clojure
Java

Server-side scripts

Stored procedures

in SQL-layer only

yes

Event Listeners, Executor Services

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

yes, but depending on the SQL-Server Edition

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Linearizable consistency

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Immediate Consistency

Foreign keys

Referential integrity

in SQL-layer only

yes

Transaction concepts

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

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

Role-based access control

fine grained access rights according to SQL-standard

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