DBMS > AlaSQL vs. Amazon DynamoDB vs. Amazon Neptune vs. etcd vs. GridGain

System Properties Comparison AlaSQL vs. Amazon DynamoDB vs. Amazon Neptune vs. etcd vs. GridGain

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

Fast, reliable graph database built for the cloud

A distributed reliable key-value store

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

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Graph DBMS
RDF store

Key-value store

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	2.20
Rank	#119	Overall
	#9	Graph DBMS
	#5	RDF stores

Score	7.25
Rank	#54	Overall
	#5	Key-value stores

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

Website

alasql.org

aws.amazon.com/dynamodb

aws.amazon.com/neptune

etcd.io
github.com/etcd-io/etcd

www.gridgain.com

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/dynamodb

aws.amazon.com/neptune/developer-resources

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

www.gridgain.com/docs/index.html

Developer

Andrey Gershun & Mathias R. Wulff

Amazon

GridGain Systems, Inc.

Initial release

2014

2012

2017

2007

Current release

3.4, August 2019

GridGain 8.5.1

License

Commercial or Open Source

Open Source

MIT-License

commercial

free tier for a limited amount of database operations

commercial

Open Source

Apache Version 2.0

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

JavaScript

Java, C++, .Net

Server operating systems

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

hosted

FreeBSD
Linux
Windows

experimental

Linux
OS X
Solaris
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

SQL

Support of SQL

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

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

APIs and other access methods

JavaScript API

RESTful HTTP API

OpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin

gRPC
JSON over HTTP

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

Supported programming languages

JavaScript

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

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

Triggers

yes

by integration with AWS Lambda

yes, watching key changes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

yes (replicated cache)

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)

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

with encyption-at-rest

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)

Security Hooks for custom implementations

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