DBMS > Amazon DynamoDB vs. Firebird vs. Stardog vs. TigerGraph

System Properties Comparison Amazon DynamoDB vs. Firebird vs. Stardog vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Firebird is an open source RDBMS forked from Borland's InterBase

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

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Document store
Key-value store

Relational DBMS

Graph DBMS
RDF store

Graph DBMS

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

Score	77.57
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	21.06
Rank	#31	Overall
	#19	Relational DBMS

Score	2.05
Rank	#129	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	1.83
Rank	#141	Overall
	#13	Graph DBMS

Website

aws.amazon.com/dynamodb

www.firebirdsql.org

www.stardog.com

www.tigergraph.com

Technical documentation

docs.aws.amazon.com/dynamodb

www.firebirdsql.org/en/reference-manuals

docs.stardog.com

docs.tigergraph.com

Developer

Amazon

Firebird Foundation

Stardog-Union

Initial release

2012

2000

As fork of Borland's InterBase

2010

2017

Current release

5.0.0, January 2024

7.3.0, May 2020

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Initial Developer's Public License

commercial

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

commercial

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 and C++

Java

C++

Server operating systems

hosted

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

Linux
macOS
Windows

Linux

Data scheme

schema-free

yes

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

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

SQL-like query language (GSQL)

APIs and other access methods

RESTful HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

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

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C++
Java

Server-side scripts

Stored procedures

PSQL

user defined functions and aggregates, HTTP Server extensions in Java

yes

Triggers

yes

by integration with AWS Lambda

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Multi-source replication in HA-Cluster

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

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

ACID across one or more tables within a single AWS account and region

ACID

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

yes

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

Users with fine-grained authorization concept

Access rights for users and roles

Role-based access control

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