DBMS > Google Cloud Spanner vs. Graph Engine vs. LokiJS vs. Microsoft Access vs. MySQL

System Properties Comparison Google Cloud Spanner vs. Graph Engine vs. LokiJS vs. Microsoft Access vs. MySQL

Editorial information provided by DB-Engines

Name

Description

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

In-memory JavaScript DBMS

Microsoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries.

The Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)

Widely used open source RDBMS

Primary database model

Relational DBMS

Graph DBMS
Key-value store

Document store

Relational DBMS

Key/Value like access via memcached API

Secondary database models

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

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

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	104.92
Rank	#11	Overall
	#8	Relational DBMS

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Website

cloud.google.com/spanner

www.graphengine.io

github.com/techfort/LokiJS

www.microsoft.com/en-us/microsoft-365/access

www.mysql.com

Technical documentation

cloud.google.com/spanner/docs

www.graphengine.io/docs/manual

techfort.github.io/LokiJS

developer.microsoft.com/en-us/access

dev.mysql.com/doc

Developer

Google

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2017

2010

2014

1992

1995

Current release

1902 (16.0.11328.20222), March 2019

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

MIT License

Open Source

commercial

Bundled with Microsoft Office

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

.NET and C

JavaScript

C++

C and C++

Server operating systems

hosted

.NET

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

Windows

Not a real database server, but making use of DLLs

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

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.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

but not compliant to any SQL standard

yes

with proprietary extensions

APIs and other access methods

gRPC (using protocol buffers) API
JDBC

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

RESTful HTTP API

JavaScript API

ADO.NET
DAO
ODBC
OLE DB

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

C#
C++
F#
Visual Basic

JavaScript

C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET

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

Server-side scripts

Stored procedures

yes

View functions in JavaScript

yes

since Access 2010 using the ACE-engine

yes

proprietary syntax

Triggers

yes

since Access 2010 using the ACE-engine

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

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

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

Strict serializable isolation

atomic operations within a single collection possible

ACID

but no files for transaction logging

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

Durability

Support for making data persistent

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

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

but no files for transaction logging

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

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

a simple user-level security was built in till version Access 2003

Users with fine-grained authorization concept

no user groups or roles

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