DBMS > Google Cloud Spanner vs. LokiJS vs. Oracle Berkeley DB vs. Oracle Coherence

System Properties Comparison Google Cloud Spanner vs. LokiJS vs. Oracle Berkeley DB vs. Oracle Coherence

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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.

In-memory JavaScript DBMS

Widely used in-process key-value store

Oracles in-memory data grid solution

Primary database model

Relational DBMS

Document store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Key-value store

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

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	0.43
Rank	#264	Overall
	#42	Document stores

Score	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

cloud.google.com/spanner

github.com/techfort/LokiJS

www.oracle.com/database/technologies/related/berkeleydb.html

www.oracle.com/java/coherence

Technical documentation

cloud.google.com/spanner/docs

techfort.github.io/LokiJS

docs.oracle.com/cd/E17076_05/html/index.html

docs.oracle.com/en/middleware/standalone/coherence

Developer

Google

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Oracle

Initial release

2017

2014

1994

2007

Current release

18.1.40, May 2020

14.1, August 2023

License

Commercial or Open Source

commercial

Open Source

commercial license available

commercial

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, Java, C++ (depending on the Berkeley DB edition)

Java

Server operating systems

hosted

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

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

All OS with a Java VM

Data scheme

yes

schema-free

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

only with the Berkeley DB XML edition

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

yes

SQL interfaced based on SQLite is available

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

JavaScript API

JCache
JPA
RESTful HTTP API

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

JavaScript

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

.Net
C++
Java

Server-side scripts

Stored procedures

View functions in JavaScript

Triggers

yes

only for the SQL API

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

none

Source-replica replication

yes, with selectable consistency level

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

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

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

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

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

yes

optionally

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)

authentification to access the cache via certificates or http basic authentication

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More resources

DB-Engines blog posts

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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