DBMS > Amazon Neptune vs. Databend vs. Firebase Realtime Database vs. MarkLogic vs. SAP HANA

System Properties Comparison Amazon Neptune vs. Databend vs. Firebase Realtime Database vs. MarkLogic vs. SAP HANA

Editorial information provided by DB-Engines

Name

Description

Fast, reliable graph database built for the cloud

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Operational and transactional Enterprise NoSQL database

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

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

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	2.29
Rank	#113	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	5.18
Rank	#63	Overall
	#11	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#7	Search engines

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Website

aws.amazon.com/neptune

github.com/datafuselabs/databend
www.databend.com

firebase.google.com/products/realtime-database

www.progress.com/marklogic

www.sap.com/products/hana.html

Technical documentation

aws.amazon.com/neptune/developer-resources

docs.databend.com

firebase.google.com/docs/database

www.progress.com/marklogic/documentation

help.sap.com/hana

Developer

Amazon

Databend Labs

Google

acquired by Google 2014

MarkLogic Corp.

SAP

Initial release

2017

2021

2012

2001

2010

Current release

1.0.59, April 2023

11.0, December 2022

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

restricted free version is available

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

Rust

C++

Server operating systems

hosted

hosted
Linux
macOS

hosted

Linux
OS X
Windows

Appliance or cloud-service

Data scheme

schema-free

yes

schema-free

Schema can be enforced

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL92

yes

APIs and other access methods

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

CLI Client
JDBC
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

JDBC
ODBC

Supported programming languages

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

Go
Java
JavaScript (Node.js)
Python
Rust

Java
JavaScript
Objective-C

C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

via XQuery or JavaScript

SQLScript, R

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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.

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

yes

ACID

can act as a resource manager in an XA/JTA transaction

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, with Range Indexes

yes

User concepts

Access control

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Users with fine-grained authorization concept, user roles

yes, based on authentication and database rules

Role-based access control at the document and subdocument levels

yes

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.