DBMS > Amazon DynamoDB vs. Hive vs. Ignite vs. OpenEdge vs. Quasardb

System Properties Comparison Amazon DynamoDB vs. Hive vs. Ignite vs. OpenEdge vs. Quasardb

Editorial information provided by DB-Engines

Name

Description

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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

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.

Application development environment with integrated database management system

Distributed, high-performance timeseries database

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store
Relational DBMS

Relational 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	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	3.45
Rank	#85	Overall
	#46	Relational DBMS

Score	0.21
Rank	#322	Overall
	#29	Time Series DBMS

Website

aws.amazon.com/dynamodb

hive.apache.org

ignite.apache.org

www.progress.com/openedge

quasar.ai

Technical documentation

docs.aws.amazon.com/dynamodb

cwiki.apache.org/confluence/display/Hive/Home

apacheignite.readme.io/docs

documentation.progress.com/output/ua/OpenEdge_latest

doc.quasar.ai/master

Developer

Amazon

Apache Software Foundation

initially developed by Facebook

Apache Software Foundation

Progress Software Corporation

quasardb

Initial release

2012

2015

1984

2009

Current release

3.1.3, April 2022

Apache Ignite 2.6

OpenEdge 12.2, March 2020

3.14.1, January 2024

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

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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

C++, Java, .Net

C++

Server operating systems

hosted

All OS with a Java VM

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
Solaris
Windows

BSD
Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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

with tags

SQL

Support of SQL

SQL-like DML and DDL statements

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

yes

close to SQL 92

SQL-like query language

APIs and other access methods

RESTful HTTP API

JDBC
ODBC
Thrift

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

JDBC
ODBC

HTTP API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Java
PHP
Python

C#
C++
Java
PHP
Python
Ruby
Scala

Progress proprietary ABL (Advanced Business Language)

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

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

yes

Triggers

yes

by integration with AWS Lambda

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

since Version 11.4

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes (replicated cache)

Source-replica replication

Source-replica replication with selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

query execution via MapReduce

yes (compute grid and hadoop accelerator)

with Hadoop integration

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

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

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Transient mode

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, groups and roles

Security Hooks for custom implementations

Users and groups

Cryptographically strong user authentication and audit trail

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