DBMS > Amazon DynamoDB vs. IBM Db2 vs. LokiJS vs. Manticore Search vs. Netezza

System Properties Comparison Amazon DynamoDB vs. IBM Db2 vs. LokiJS vs. Manticore Search vs. Netezza

Editorial information provided by DB-Engines

Name

Description

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

Common in IBM host environments, 2 different versions for host and Windows/Linux

In-memory JavaScript DBMS

Multi-storage database for search, including full-text search.

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Document store
Key-value store

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

Document store

Search engine

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Time Series DBMS

using the Manticore Columnar Library

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	125.90
Rank	#9	Overall
	#6	Relational DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Website

aws.amazon.com/dynamodb

www.ibm.com/products/db2

github.com/techfort/LokiJS

manticoresearch.com

www.ibm.com/products/netezza

Technical documentation

docs.aws.amazon.com/dynamodb

www.ibm.com/docs/en/db2

techfort.github.io/LokiJS

manual.manticoresearch.com

Developer

Amazon

IBM

Manticore Software

IBM

Initial release

2012

1983

host version

2014

2017

2000

Current release

12.1, October 2016

6.0, February 2023

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

free version is available

Open Source

GPL version 2

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

C and C++

JavaScript

C++

Server operating systems

hosted

AIX
HP-UX
Linux
Solaris
Windows
z/OS

server-less, requires a JavaScript environment (browser, Node.js)

FreeBSD
Linux
macOS
Windows

Linux

included in appliance

Data scheme

schema-free

yes

schema-free

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

via views

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

JavaScript API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

JDBC
ODBC
OLE DB

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

JavaScript

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

View functions in JavaScript

user defined functions

yes

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

only with Windows/Unix/Linux Version

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

with separate tools (MQ, InfoSphere)

none

Synchronous replication based on Galera library

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

none

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

atomic operations within a single collection possible

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

The original contents of fields are not stored in the Manticore index.

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

Users with fine-grained authorization concept

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.