DBMS > Amazon DynamoDB vs. EsgynDB vs. InterSystems IRIS vs. Kdb vs. Solr

System Properties Comparison Amazon DynamoDB vs. EsgynDB vs. InterSystems IRIS vs. Kdb vs. Solr

Editorial information provided by DB-Engines

Name

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

High performance Time Series DBMS

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS
Vector DBMS

Search engine

Secondary database models

Relational DBMS

Spatial DBMS

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	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	4.05
Rank	#83	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	7.55
Rank	#53	Overall
	#3	Time Series DBMS
	#1	Vector DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

aws.amazon.com/dynamodb

www.esgyn.cn

www.intersystems.com/products/intersystems-iris

kx.com

solr.apache.org

Technical documentation

docs.aws.amazon.com/dynamodb

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

code.kx.com

solr.apache.org/resources.html

Developer

Amazon

Esgyn

InterSystems

Kx Systems, a division of First Derivatives plc

Apache Software Foundation

Initial release

2012

2015

2018

2000

kdb was released 2000, kdb+ in 2003

2006

Current release

2023.3, June 2023

3.6, May 2018

9.6.0, April 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free 32-bit version

Open Source

Apache Version 2

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

Java

Server operating systems

hosted

Linux

AIX
Linux
macOS
Ubuntu
Windows

Linux
OS X
Solaris
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

schema-free

yes

depending on used data model

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

supports customizable data types and automatic typing

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

table attribute 'grouped'

yes

All search fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language (q)

Solr Parallel SQL Interface

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
ODBC

JDBC
ODBC
RESTful HTTP API

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

Java API
RESTful HTTP/JSON API

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

All languages supporting JDBC/ODBC/ADO.Net

.Net
C++
Java
JavaScript (Node.js)
Python

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

Java Stored Procedures

yes

user defined functions

Java plugins

Triggers

yes

by integration with AWS Lambda

yes

with views

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

similar paradigm used for internal processing

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Eventual 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

optimistic locking

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

yes

rights management via user accounts

yes

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
» more

Integrated columnar database & programming system for streaming, real time and historical...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
» more

Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
» more

Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
» more

Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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Licensing and pricing models

upon request
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.