DBMS > AlaSQL vs. Amazon DynamoDB vs. GridDB vs. GridGain vs. SAP SQL Anywhere

System Properties Comparison AlaSQL vs. Amazon DynamoDB vs. GridDB vs. GridGain vs. SAP SQL Anywhere

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

Scalable in-memory time series database optimized for IoT and Big Data

GridGain is an in-memory computing platform, built on Apache Ignite

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Key-value store
Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.46
Rank	#260	Overall
	#40	Document stores
	#121	Relational DBMS

Score	74.07
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.95
Rank	#128	Overall
	#10	Time Series DBMS

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	4.25
Rank	#79	Overall
	#43	Relational DBMS

Website

alasql.org

aws.amazon.com/dynamodb

griddb.net

www.gridgain.com

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/dynamodb

docs.griddb.net

www.gridgain.com/docs/index.html

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Andrey Gershun & Mathias R. Wulff

Amazon

Toshiba Corporation

GridGain Systems, Inc.

SAP

formerly Sybase

Initial release

2014

2012

2013

2007

1992

Current release

5.1, August 2022

GridGain 8.5.1

17, July 2015

License

Commercial or Open Source

Open Source

MIT-License

commercial

free tier for a limited amount of database operations

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

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

JavaScript

C++

Java, C++, .Net

Server operating systems

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

hosted

Linux

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

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

SQL

Support of SQL

Close to SQL99, but no user access control, stored procedures and host language bindings.

SQL92, SQL-like TQL (Toshiba Query Language)

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

yes

APIs and other access methods

JavaScript API

RESTful HTTP API

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

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

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

JavaScript

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

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

yes, in C/C++, Java, .Net or Perl

Triggers

yes

by integration with AWS Lambda

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

yes (replicated cache)

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

yes

only for local storage and DOM-storage

ACID

ACID across one or more tables within a single AWS account and region

ACID at container level

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

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)

Access rights for users can be defined per database

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more

Competitive advantages

1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
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Typical application scenarios

Factory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more

Key customers

Denso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more

Market metrics

GitHub trending repository
» more

Licensing and pricing models

Open Source license (AGPL v3 & Apache v2) Commercial license (subscription)
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