DBMS > Amazon Neptune vs. FoundationDB vs. LeanXcale vs. MaxDB vs. SAP HANA

System Properties Comparison Amazon Neptune vs. FoundationDB vs. LeanXcale vs. MaxDB vs. SAP HANA

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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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, reliable graph database built for the cloud

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

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

A robust and reliable RDBMS optimized to run all major SAP solutions

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Graph DBMS
RDF store

Document store

supported via specific layer
Key-value store
Relational DBMS

supported via specific SQL-layer

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

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

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

aws.amazon.com/neptune

github.com/apple/foundationdb

www.leanxcale.com

maxdb.sap.com

www.sap.com/products/hana.html

Technical documentation

aws.amazon.com/neptune/developer-resources

apple.github.io/foundationdb

maxdb.sap.com/documentation

help.sap.com/hana

Developer

Amazon

FoundationDB

LeanXcale

SAP, acquired from Software AG (Adabas-D) in 1997

SAP

Initial release

2017

2013

2015

1984

2010

Current release

6.2.28, November 2020

7.9.10.12, February 2024

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Limited community edition free

commercial

Cloud-based only

Only available as a cloud service

yes

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

hosted

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

Appliance or cloud-service

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

through Apache Derby

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

ADO.NET
JDBC
ODBC
WebDAV

JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C
C++
Go
Java
JavaScript

Node.js
PHP
Python
Ruby
Swift

C
Java
Scala

.Net
C#
Java
Perl
PHP
Python

Server-side scripts

Stored procedures

in SQL-layer only

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

yes

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Linearizable consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

in SQL-layer only

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with encyption-at-rest

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 can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

yes

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