DBMS > AlaSQL vs. Google Cloud Datastore vs. Graph Engine vs. Memcached vs. Oracle

System Properties Comparison AlaSQL vs. Google Cloud Datastore vs. Graph Engine vs. Memcached vs. Oracle

Editorial information provided by DB-Engines

Name

Description

JavaScript DBMS library

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

In-memory key-value store, originally intended for caching

Widely used RDBMS

Primary database model

Document store
Relational DBMS

Document store

Graph DBMS
Key-value store

Key-value store

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	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	1236.29
Rank	#1	Overall
	#1	Relational DBMS

Website

alasql.org

cloud.google.com/datastore

www.graphengine.io

www.memcached.org

www.oracle.com/database

Technical documentation

github.com/AlaSQL/alasql

cloud.google.com/datastore/docs

www.graphengine.io/docs/manual

github.com/memcached/memcached/wiki

docs.oracle.com/en/database

Developer

Andrey Gershun & Mathias R. Wulff

Google

Microsoft

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

Oracle

Initial release

2014

2008

2010

2003

1980

Current release

1.6.25, March 2024

23c, September 2023

License

Commercial or Open Source

Open Source

MIT-License

commercial

Open Source

MIT License

Open Source

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

.NET and C

C and C++

Server operating systems

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

hosted

.NET

FreeBSD
Linux
OS X
Unix
Windows

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

Data scheme

schema-free

yes

schema-free

yes

Schemaless in JSON and XML columns

Typing

predefined data types such as float or date

yes, details here

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.

SQL-like query language (GQL)

yes

with proprietary extensions

APIs and other access methods

JavaScript API

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

RESTful HTTP API

Proprietary protocol

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

JavaScript

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C#
C++
F#
Visual Basic

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

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

using Google App Engine

yes

PL/SQL

also stored procedures in Java possible

Triggers

yes

Callbacks using the Google Apps Engine

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

none

Sharding, horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication using Paxos

none

Repcached, a Memcached patch, provides this functionallity

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 or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

yes

via ReferenceProperties or Ancestor paths

yes

Transaction concepts

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

yes

only for local storage and DOM-storage

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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)

yes

using SASL (Simple Authentication and Security Layer) protocol

fine grained access rights according to SQL-standard

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