DBMS > Alibaba Cloud AnalyticDB for MySQL vs. Dgraph vs. LokiJS vs. Oracle Berkeley DB vs. TimescaleDB

System Properties Comparison Alibaba Cloud AnalyticDB for MySQL vs. Dgraph vs. LokiJS vs. Oracle Berkeley DB vs. TimescaleDB

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.

Distributed and scalable native Graph DBMS

In-memory JavaScript DBMS

Widely used in-process key-value store

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Time Series 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	1.45
Rank	#156	Overall
	#15	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	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

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

dgraph.io

github.com/techfort/LokiJS

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

www.timescale.com

Technical documentation

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

dgraph.io/docs

techfort.github.io/LokiJS

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

docs.timescale.com

Developer

Alibaba

Dgraph Labs, Inc.

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Timescale

Initial release

2016

2014

1994

2017

Current release

18.1.40, May 2020

2.13.0, November 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

commercial license available

Open Source

Apache 2.0

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)

Server operating systems

hosted

Linux
OS X
Windows

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

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

full PostgreSQL SQL syntax

APIs and other access methods

JDBC
ODBC

GraphQL query language
gRPC (using protocol buffers) API
HTTP API

JavaScript API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

C#
Java
PHP
Python

C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

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
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

View functions in JavaScript

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

only for the SQL API

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

yes

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

Synchronous replication via Raft

none

Source-replica replication

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Immediate Consistency

Foreign keys

Referential integrity

yes

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

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

Planned for future releases

fine grained access rights according to SQL-standard

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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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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