DBMS > Amazon DynamoDB vs. Derby vs. Ignite vs. InfinityDB

System Properties Comparison Amazon DynamoDB vs. Derby vs. Ignite vs. InfinityDB

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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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

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

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store
Relational DBMS

Key-value 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	4.71
Rank	#69	Overall
	#37	Relational DBMS

Score	3.16
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	0.00
Rank	#378	Overall
	#57	Key-value stores

Website

aws.amazon.com/dynamodb

db.apache.org/derby

ignite.apache.org

boilerbay.com

Technical documentation

docs.aws.amazon.com/dynamodb

db.apache.org/derby/manuals/index.html

apacheignite.readme.io/docs

boilerbay.com/infinitydb/manual

Developer

Amazon

Apache Software Foundation

Boiler Bay Inc.

Initial release

2012

1997

2015

2002

Current release

10.17.1.0, November 2023

Apache Ignite 2.6

4.0

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

Apache version 2

Open Source

Apache 2.0

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

Java

C++, Java, .Net

Java

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Solaris
Windows

All OS with a Java VM

Data scheme

schema-free

yes

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

Typing

predefined data types such as float or date

yes

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

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

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

SQL

Support of SQL

yes

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

APIs and other access methods

RESTful HTTP API

JDBC

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

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

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java

C#
C++
Java
PHP
Python
Ruby
Scala

Java

Server-side scripts

Stored procedures

Java Stored Procedures

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

Triggers

yes

by integration with AWS Lambda

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes (replicated cache)

none

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

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

yes

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

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

Optimistic locking for transactions; no isolation for bulk loads

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.

yes

User concepts

Access control

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

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

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