DBMS > AlaSQL vs. Google BigQuery vs. Graphite vs. Oracle vs. VoltDB

System Properties Comparison AlaSQL vs. Google BigQuery vs. Graphite vs. Oracle vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Large scale data warehouse service with append-only tables

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

Widely used RDBMS

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store
Relational DBMS

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

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	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

alasql.org

cloud.google.com/bigquery

github.com/graphite-project/graphite-web

www.oracle.com/database

www.voltdb.com

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/bigquery/docs

graphite.readthedocs.io

docs.oracle.com/en/database

docs.voltdb.com

Developer

Andrey Gershun & Mathias R. Wulff

Google

Chris Davis

Oracle

VoltDB Inc.

Initial release

2014

2010

2006

1980

2010

Current release

23c, September 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

Apache 2.0

commercial

restricted free version is available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

Python

C and C++

Java, C++

Server operating systems

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

hosted

Linux
Unix

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

Linux
OS X

for development

Data scheme

schema-free

yes

Schemaless in JSON and XML columns

yes

Typing

predefined data types such as float or date

yes

Numeric data only

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

with proprietary extensions

yes

only a subset of SQL 99

APIs and other access methods

JavaScript API

RESTful HTTP/JSON API

HTTP API
Sockets

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

JavaScript

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

JavaScript (Node.js)
Python

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

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

PL/SQL

also stored procedures in Java possible

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding, horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

can be realized in PL/SQL

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

yes

only for local storage and DOM-storage

Since BigQuery is designed for querying data

ACID

isolation level can be parameterized

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

by using IndexedDB, SQL.JS or proprietary FileStorage

yes

Snapshots and command logging

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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