DBMS > Amazon DocumentDB vs. SAP HANA vs. SiriDB vs. Stardog vs. Vitess

System Properties Comparison Amazon DocumentDB vs. SAP HANA vs. SiriDB vs. Stardog vs. Vitess

Editorial information provided by DB-Engines

Name

Description

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

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

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Document store
Spatial DBMS

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

Score	1.91
Rank	#131	Overall
	#24	Document stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

aws.amazon.com/documentdb

www.sap.com/products/hana.html

siridb.com

www.stardog.com

vitess.io

Technical documentation

aws.amazon.com/documentdb/resources

Developer

SAP

Cesbit

Stardog-Union

The Linux Foundation, PlanetScale

Initial release

2019

2010

2017

2010

2013

Current release

2.0 SPS07 (April 4, 2023), April 2023

7.3.0, May 2020

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

Apache Version 2.0, commercial licenses available

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

Java

Server operating systems

hosted

Appliance or cloud-service

Linux

Linux
macOS
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

Numeric data

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

yes

with proprietary extensions

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC

HTTP API

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

SQLScript, R

user defined functions and aggregates, HTTP Server extensions in Java

yes

proprietary syntax

Triggers

yes

via event handlers

yes

Partitioning methods

Methods for storing different data on different nodes

none

yes

Sharding

none

Sharding

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

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

yes

relationships in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

Atomic single-document operations

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

yes

simple rights management via user accounts

Access rights for users and roles

Users with fine-grained authorization concept

no user groups or roles

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.