DBMS > AlaSQL vs. GeoMesa vs. Riak TS vs. Spark SQL

System Properties Comparison AlaSQL vs. GeoMesa vs. Riak TS vs. Spark SQL

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Document store
Relational DBMS

Spatial DBMS

Time Series DBMS

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	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Website

alasql.org

www.geomesa.org

spark.apache.org/sql

Technical documentation

github.com/AlaSQL/alasql

www.geomesa.org/documentation/stable/user/index.html

www.tiot.jp/riak-docs/riak/ts/latest

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Andrey Gershun & Mathias R. Wulff

CCRi and others

Open Source, formerly Basho Technologies

Apache Software Foundation

Initial release

2014

2015

2014

Current release

5.0.0, May 2024

3.0.0, September 2022

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache License 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

JavaScript

Scala

Erlang

Scala

Server operating systems

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

Linux
OS X

Linux
OS X
Windows

Data scheme

schema-free

yes

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

restricted

SQL

Support of SQL

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

yes, limited

SQL-like DML and DDL statements

APIs and other access methods

JavaScript API

HTTP API
Native Erlang Interface

JDBC
ODBC

Supported programming languages

JavaScript

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Java
Python
R
Scala

Server-side scripts

Stored procedures

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

depending on storage layer

Eventual Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

yes

only for local storage and DOM-storage

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

depending on storage layer

User concepts

Access control

yes

depending on the DBMS used for storage

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

show all

Recent citations in the news

HarperDB - How and Why We Built It From The Ground Up on NodeJS
28 February 2021, hackernoon.com

Create a Marvel Database with SQL and Javascript, the easy way
2 July 2019, Towards Data Science

Multi faceted data exploration in the browser using Leaflet and amCharts
3 May 2020, Towards Data Science

provided by Google News

New Basho Data Platform Provides Operational Simplicity for Enterprise Big Data Applications
7 June 2015, insideBIGDATA

Best open source databases for IoT applications
26 May 2017, Open Source For You

provided by Google News

Run Apache Hive workloads using Spark SQL with Amazon EMR on EKS | Amazon Web Services
18 October 2023, AWS Blog

Performance Insights from Sigma Rule Detections in Spark Streaming
1 June 2024, Towards Data Science

Cracking the Apache Spark Interview: 80+ Top Questions and Answers for 2024
1 April 2024, Simplilearn

18 Top Big Data Tools and Technologies to Know About in 2024
24 January 2024, TechTarget

Use Amazon Athena with Spark SQL for your open-source transactional table formats | Amazon Web Services
24 January 2024, AWS Blog

provided by Google News

Share this page