DBMS > AlaSQL vs. Amazon DynamoDB vs. EXASOL vs. HyperSQL vs. Splice Machine

System Properties Comparison AlaSQL vs. Amazon DynamoDB vs. EXASOL vs. HyperSQL vs. Splice Machine

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

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

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

Document store
Relational DBMS

Document store
Key-value store

Relational DBMS

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

Score	0.51
Rank	#256	Overall
	#40	Document stores
	#118	Relational DBMS

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	3.23
Rank	#93	Overall
	#48	Relational DBMS

Score	0.54
Rank	#252	Overall
	#115	Relational DBMS

Website

alasql.org

aws.amazon.com/dynamodb

www.exasol.com

hsqldb.org

splicemachine.com

Technical documentation

github.com/AlaSQL/alasql

docs.aws.amazon.com/dynamodb

www.exasol.com/resources

hsqldb.org/web/hsqlDocsFrame.html

splicemachine.com/how-it-works

Developer

Andrey Gershun & Mathias R. Wulff

Amazon

Exasol

Splice Machine

Initial release

2014

2012

2000

2001

2014

Current release

2.7.2, June 2023

3.1, March 2021

License

Commercial or Open Source

Open Source

MIT-License

commercial

free tier for a limited amount of database operations

commercial

Open Source

based on BSD license

Open Source

AGPL 3.0, commercial license 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

Server operating systems

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

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

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.

Secondary indexes

yes

SQL

Support of SQL

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

yes

APIs and other access methods

JavaScript API

RESTful HTTP API

.Net
JDBC
ODBC
WebSocket

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
Native Spark Datasource
ODBC

Supported programming languages

JavaScript

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

Java
Lua
Python
R

All languages supporting JDBC/ODBC
Java

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

user defined functions

Java, SQL

yes

Java

Triggers

yes

by integration with AWS Lambda

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Hadoop integration

Yes, via Full Spark Integration

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

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

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