DBMS > Amazon DynamoDB vs. GBase vs. Ignite vs. Kdb vs. Sadas Engine

System Properties Comparison Amazon DynamoDB vs. GBase vs. Ignite vs. Kdb vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

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.

High performance Time Series DBMS

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Document store
Key-value store

Relational DBMS

Key-value store
Relational DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational 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	1.05
Rank	#186	Overall
	#86	Relational DBMS

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

Score	7.71
Rank	#49	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	0.07
Rank	#373	Overall
	#157	Relational DBMS

Website

aws.amazon.com/dynamodb

Technical documentation

docs.aws.amazon.com/dynamodb

apacheignite.readme.io/docs

code.kx.com

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Amazon

General Data Technology Co., Ltd.

Apache Software Foundation

Kx Systems, a division of First Derivatives plc

SADAS s.r.l.

Initial release

2012

2004

2015

2000

kdb was released 2000, kdb+ in 2003

2006

Current release

GBase 8a, GBase 8s, GBase 8c

Apache Ignite 2.6

3.6, May 2018

8.0

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache 2.0

commercial

free 32-bit version

commercial

free trial version available

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, Python

C++, Java, .Net

C++

Server operating systems

hosted

Linux

Linux
OS X
Solaris
Windows

AIX
Linux
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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.

yes

Secondary indexes

yes

table attribute 'grouped'

yes

SQL

Support of SQL

Standard with numerous extensions

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

SQL-like query language (q)

yes

APIs and other access methods

RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

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

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

JDBC
ODBC
Proprietary protocol

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

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

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

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

user defined functions

Triggers

yes

by integration with AWS Lambda

yes

yes (cache interceptors and events)

yes

with views

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

Source-replica replication

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)

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

In-memory capabilities

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

yes

managed by 'Learn by Usage'

User concepts

Access control

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

yes

Security Hooks for custom implementations

rights management via user accounts

Access rights for users, groups and roles according to SQL-standard

More information provided by the system vendor

Specific characteristics

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...
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Typical application scenarios

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