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

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

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

A distributed reliable key-value store

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

Operational and transactional Enterprise NoSQL database

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Key-value store

Key-value store
Relational DBMS

Document store
Native XML DBMS
RDF store

as of version 7
Search engine

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	7.25
Rank	#54	Overall
	#5	Key-value stores

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

Score	5.92
Rank	#58	Overall
	#10	Document stores
	#1	Native XML DBMS
	#1	RDF stores
	#6	Search engines

Website

alasql.org

aws.amazon.com/dynamodb

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

www.gridgain.com

www.marklogic.com

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/dynamodb

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

www.gridgain.com/docs/index.html

docs.marklogic.com

Developer

Andrey Gershun & Mathias R. Wulff

Amazon

GridGain Systems, Inc.

MarkLogic Corp.

Initial release

2014

2012

2007

2001

Current release

3.4, August 2019

GridGain 8.5.1

11.0, December 2022

License

Commercial or Open Source

Open Source

MIT-License

commercial

free tier for a limited amount of database operations

Open Source

Apache Version 2.0

commercial

restricted free version is 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

JavaScript

Java, C++, .Net

C++

Server operating systems

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

hosted

FreeBSD
Linux
Windows

experimental

Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Schema can be enforced

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

yes

SQL92

APIs and other access methods

JavaScript API

RESTful HTTP API

gRPC
JSON over HTTP

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

Java API
Node.js Client API
ODBC
proprietary Optic API

Proprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT

Supported programming languages

JavaScript

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

.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

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

Server-side scripts

Stored procedures

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

yes

via XQuery or JavaScript

Triggers

yes

by integration with AWS Lambda

yes, watching key changes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

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

yes (replicated cache)

yes

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)

yes

via Hadoop Connector, HDFS Direct Access and in-database MapReduce jobs

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

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

can act as a resource manager in an XA/JTA transaction

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

yes, with Range Indexes

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

Role-based access control at the document and subdocument levels

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