DBMS > AlaSQL vs. GeoMesa vs. MySQL vs. Splice Machine vs. Teradata

System Properties Comparison AlaSQL vs. GeoMesa vs. MySQL vs. Splice Machine vs. Teradata

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.

Widely used open source RDBMS

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

A hybrid cloud data analytics software platform (Teradata Vantage)

Primary database model

Document store
Relational DBMS

Spatial DBMS

Relational DBMS

Key/Value like access via memcached API

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
Graph DBMS
Spatial DBMS
Time Series 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	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	45.33
Rank	#21	Overall
	#15	Relational DBMS

Website

Technical documentation

github.com/AlaSQL/alasql

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

dev.mysql.com/doc

splicemachine.com/how-it-works

docs.teradata.com

Developer

Andrey Gershun & Mathias R. Wulff

CCRi and others

Oracle

since 2010, originally MySQL AB, then Sun

Splice Machine

Teradata

Initial release

2014

1995

2014

1984

Current release

4.0.5, February 2024

8.4.0, April 2024

3.1, March 2021

Teradata Vantage 1.0 MU2, January 2019

License

Commercial or Open Source

Open Source

MIT-License

Open Source

Apache License 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

AGPL 3.0, commercial license available

commercial

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

JavaScript

Scala

C and C++

Java

Server operating systems

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

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

hosted
Linux

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

Join-index to prejoin tables, aggregate index, sparse index, hash index

SQL

Support of SQL

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

yes

with proprietary extensions

yes

SQL 2016 + extensions

APIs and other access methods

JavaScript API

ADO.NET
JDBC
ODBC
Proprietary native API

JDBC
Native Spark Datasource
ODBC

.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB

Supported programming languages

JavaScript

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

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

C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Java

yes

UDFs, stored procedures, table functions in parallel

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

depending on storage layer

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Shared Nothhing Auto-Sharding, Columnar Partitioning

Sharding

Hashing

Replication methods

Methods for redundantly storing data on multiple nodes

none

depending on storage layer

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

none

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes, multi-version concurrency control (MVCC)

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

yes

User concepts

Access control

yes

depending on the DBMS used for storage

Users with fine-grained authorization concept

no user groups or roles

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

fine grained access rights according to SQL-standard

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