DBMS > AlaSQL vs. Google Cloud Spanner vs. HEAVY.AI vs. HyperSQL vs. Oracle

System Properties Comparison AlaSQL vs. Google Cloud Spanner vs. HEAVY.AI vs. HyperSQL vs. Oracle

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Widely used RDBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS

with Oracle Spatial and Graph
RDF store

with Oracle Spatial and Graph
Spatial DBMS

with Oracle Spatial and Graph
Vector DBMS

since Oracle 23

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	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

alasql.org

cloud.google.com/spanner

github.com/heavyai/heavydb
www.heavy.ai

hsqldb.org

www.oracle.com/database

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/spanner/docs

docs.heavy.ai

hsqldb.org/web/hsqlDocsFrame.html

docs.oracle.com/en/database

Developer

Andrey Gershun & Mathias R. Wulff

Google

HEAVY.AI, Inc.

Oracle

Initial release

2014

2017

2016

2001

1980

Current release

5.10, January 2022

2.7.2, June 2023

23c, September 2023

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

based on BSD license

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

C++ and CUDA

Java

C and C++

Server operating systems

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

hosted

Linux

All OS with a Java VM

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

AIX
HP-UX
Linux
OS X
Solaris
Windows
z/OS

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

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.

yes

Query statements complying to ANSI 2011

yes

with proprietary extensions

APIs and other access methods

JavaScript API

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC
Thrift
Vega

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

JavaScript

Go
Java
JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/Thrift
Python

All languages supporting JDBC/ODBC
Java

C
C#
C++
Clojure
Cobol
Delphi
Eiffel
Erlang
Fortran
Groovy
Haskell
Java
JavaScript
Lisp
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Scala
Tcl
Visual Basic

Server-side scripts

Stored procedures

Java, SQL

PL/SQL

also stored procedures in Java possible

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Round robin

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication with 3 replicas for regional instances.

Multi-source replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on 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

Strict serializable isolation

ACID

isolation level can be parameterized

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

Version 12c introduced the new option 'Oracle Database In-Memory'

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

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