DBMS > Amazon DynamoDB vs. GridDB vs. H2GIS vs. InfinityDB vs. TerminusDB

System Properties Comparison Amazon DynamoDB vs. GridDB vs. H2GIS vs. InfinityDB vs. TerminusDB

Editorial information provided by DB-Engines

Name

Description

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

Scalable in-memory time series database optimized for IoT and Big Data

Spatial extension of H2

A Java embedded Key-Value Store which extends the Java Map interface

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

Primary database model

Document store
Key-value store

Secondary database models

Key-value store
Relational DBMS

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	2.09
Rank	#120	Overall
	#10	Time Series DBMS

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.08
Rank	#365	Overall
	#55	Key-value stores

Score	0.23
Rank	#316	Overall
	#27	Graph DBMS

Website

aws.amazon.com/dynamodb

Technical documentation

docs.aws.amazon.com/dynamodb

docs.griddb.net

www.h2gis.org/docs/home

boilerbay.com/infinitydb/manual

terminusdb.github.io/terminusdb/#

Developer

Amazon

Toshiba Corporation

CNRS

Boiler Bay Inc.

DataChemist Ltd.

Initial release

2012

2013

2002

2018

Current release

5.1, August 2022

4.0

11.0.0, January 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

Open Source

LGPL 3.0

commercial

Open Source

GPL V3

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++

Java

Prolog, Rust

Server operating systems

hosted

Linux

All OS with a Java VM

Linux

Data scheme

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

yes

SQL-like query language (WOQL)

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

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

Java

JavaScript
Python

Server-side scripts

Stored procedures

yes

based on H2

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes

based on H2

none

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

yes

manual creation possible, using inversions based on multi-value capability

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 at container level

ACID

Optimistic locking for transactions; no isolation for bulk loads

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

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)

Access rights for users can be defined per database

yes

based on H2

Role-based access control

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more

Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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