DBMS > Alibaba Cloud AnalyticDB for MySQL vs. JanusGraph vs. LokiJS vs. Oracle Berkeley DB vs. SpaceTime

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. JanusGraph vs. LokiJS vs. Oracle Berkeley DB vs. SpaceTime

Editorial information provided by DB-Engines

Name

Description

A real-time data warehousing service that can process petabytes of data with high concurrency and low latency. It is fully compatible with the MySQL protocol.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

In-memory JavaScript DBMS

Widely used in-process key-value store

SpaceTime is a spatio-temporal DBMS with a focus on performance.

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Spatial DBMS

Secondary database models

Document store

Relational DBMS

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

Score	0.85
Rank	#207	Overall
	#96	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph 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	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Website

www.alibabacloud.com/product/analyticdb-for-mysql

janusgraph.org

github.com/techfort/LokiJS

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

www.mireo.com/spacetime

Technical documentation

www.alibabacloud.com/help/doc-detail/93776.htm

docs.janusgraph.org

techfort.github.io/LokiJS

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

Developer

Alibaba

Linux Foundation; originally developed as Titan by Aurelius

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Mireo

Initial release

2017

2014

1994

2020

Current release

0.6.3, February 2023

18.1.40, May 2020

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

Java

JavaScript

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

C++

Server operating systems

hosted

Linux
OS X
Unix
Windows

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

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux

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

only with the Berkeley DB XML edition

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

A subset of ANSI SQL is implemented

APIs and other access methods

JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JavaScript API

RESTful HTTP API

Supported programming languages

C#
Java
PHP
Python

Clojure
Java
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

C#
C++
Python

Server-side scripts

Stored procedures

yes

View functions in JavaScript

Triggers

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Fixed-grid hypercubes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes

none

Source-replica replication

Real-time block device replication (DRBD)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

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

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

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

yes

More information provided by the system vendor

Specific characteristics

A real-time data warehousing service that can process PB data with high concurrency...
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Competitive advantages

TPC Benchmark: The world leading result in TPC-DS benchmark . TPC-H benchmark for...
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Licensing and pricing models

Available regions: America US Virginia US Silicon Valley Asia China Hong Kong India...
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