DBMS > Amazon DynamoDB vs. Drizzle vs. GigaSpaces vs. Warp 10

System Properties Comparison Amazon DynamoDB vs. Drizzle vs. GigaSpaces vs. Warp 10

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

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

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Document store
Key-value store

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Time Series DBMS

Secondary database models

Graph DBMS
Search engine

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	0.97
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/dynamodb

www.gigaspaces.com

www.warp10.io

Technical documentation

docs.aws.amazon.com/dynamodb

docs.gigaspaces.com/latest/landing.html

www.warp10.io/content/02_Getting_started

Developer

Amazon

Drizzle project, originally started by Brian Aker

Gigaspaces Technologies

SenX

Initial release

2012

2008

2000

2015

Current release

7.2.4, September 2012

15.5, September 2020

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

GNU GPL

Open Source

Apache Version 2; Commercial licenses available

Open Source

Apache License 2.0

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, C++, .Net

Java

Server operating systems

hosted

FreeBSD
Linux
OS X

Linux
macOS
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

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.

XML can be used for describing objects metadata

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-99 for query and DML statements

APIs and other access methods

RESTful HTTP API

JDBC

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

HTTP API
Jupyter
WebSocket

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Java
PHP

.Net
C++
Java
Python
Scala

Server-side scripts

Stored procedures

yes

WarpScript

Triggers

yes

by integration with AWS Lambda

hooks for callbacks inside the server can be used.

yes, event driven architecture

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

based on HBase

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

User concepts

Access control

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

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Role-based access control

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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