DBMS > Amazon DynamoDB vs. GeoMesa vs. RavenDB vs. TigerGraph vs. Trafodion

System Properties Comparison Amazon DynamoDB vs. GeoMesa vs. RavenDB vs. TigerGraph vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Key-value store

Secondary database models

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	2.84
Rank	#101	Overall
	#18	Document stores

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

aws.amazon.com/dynamodb

Technical documentation

docs.aws.amazon.com/dynamodb

www.geomesa.org/documentation/stable/user/index.html

ravendb.net/docs

docs.tigergraph.com

trafodion.apache.org/documentation.html

Developer

Amazon

CCRi and others

Hibernating Rhinos

Apache Software Foundation, originally developed by HP

Initial release

2012

2014

2010

2017

2014

Current release

5.0.0, May 2024

5.4, July 2022

2.3.0, February 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache License 2.0

Open Source

AGPL version 3, commercial license available

commercial

Open Source

Apache 2.0

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

Scala

C++

C++, Java

Server operating systems

hosted

Linux
macOS
Raspberry Pi
Windows

Linux

Data scheme

schema-free

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language (RQL)

SQL-like query language (GSQL)

yes

APIs and other access methods

RESTful HTTP API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

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

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Java

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes

Java Stored Procedures

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

Multi-source replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

depending on storage layer

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

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

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

ACID, Cluster-wide transaction available

ACID

Concurrency

Support for concurrent manipulation of data

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.

depending on storage layer

User concepts

Access control

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

yes

depending on the DBMS used for storage

Authorization levels configured per client per database

Role-based access control

fine grained access rights according to SQL-standard

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