DBMS > Amazon DynamoDB vs. Geode vs. GridGain vs. XTDB

System Properties Comparison Amazon DynamoDB vs. Geode vs. GridGain vs. XTDB

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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

Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processes

GridGain is an in-memory computing platform, built on Apache Ignite

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Key-value store

Key-value store

Key-value store
Relational DBMS

Document store

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

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.92
Rank	#131	Overall
	#23	Key-value stores

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

aws.amazon.com/dynamodb

geode.apache.org

www.gridgain.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.aws.amazon.com/dynamodb

geode.apache.org/docs

www.gridgain.com/docs/index.html

www.xtdb.com/docs

Developer

Amazon

Originally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.

GridGain Systems, Inc.

Juxt Ltd.

Initial release

2012

2002

2007

2019

Current release

1.1, February 2017

GridGain 8.5.1

1.19, September 2021

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2; commercial licenses available as Gemfire

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Java, C++, .Net

Clojure

Server operating systems

hosted

All OS with a Java VM

the JDK (8 or later) is also required

Linux
OS X
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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

SQL-like query language (OQL)

ANSI-99 for query and DML statements, subset of DDL

limited SQL, making use of Apache Calcite

APIs and other access methods

RESTful HTTP API

Java Client API
Memcached protocol
RESTful HTTP API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

HTTP REST
JDBC

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.Net
All JVM based languages
C++
Groovy
Java
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

Clojure
Java

Server-side scripts

Stored procedures

user defined functions

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

by integration with AWS Lambda

yes

Cache Event Listeners

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes (replicated cache)

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

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

yes, on a single node

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 per client and object definable

Security Hooks for custom implementations

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