DBMS > Amazon DynamoDB vs. Databricks vs. H2GIS vs. TerminusDB vs. Trafodion

System Properties Comparison Amazon DynamoDB vs. Databricks vs. H2GIS vs. TerminusDB 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

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

Spatial extension of H2

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Key-value store

Document store
Relational DBMS

Spatial DBMS

Graph DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
RDF store

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	81.08
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

aws.amazon.com/dynamodb

Technical documentation

docs.aws.amazon.com/dynamodb

docs.databricks.com

www.h2gis.org/docs/home

terminusdb.github.io/terminusdb/#

trafodion.apache.org/documentation.html

Developer

Amazon

Databricks

CNRS

DataChemist Ltd.

Apache Software Foundation, originally developed by HP

Initial release

2012

2013

2018

2014

Current release

11.0.0, January 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

LGPL 3.0

Open Source

GPL V3

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

Java

Prolog, Rust

C++, Java

Server operating systems

hosted

Linux

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, 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.

yes

Secondary indexes

yes

SQL

Support of SQL

with Databricks SQL

yes

SQL-like query language (WOQL)

yes

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

ADO.NET
JDBC
ODBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Python
R
Scala

Java

JavaScript
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions and aggregates

yes

based on H2

yes

Java Stored Procedures

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

Journaling Streams

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

Immediate Consistency

Foreign keys

Referential integrity

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

in-memory journaling

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)

yes

based on H2

Role-based access control

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
» more

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.