DBMS > AgensGraph vs. Google Cloud Firestore vs. NSDb vs. Oracle Berkeley DB

System Properties Comparison AgensGraph vs. Google Cloud Firestore vs. NSDb vs. Oracle Berkeley DB

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Widely used in-process key-value store

Primary database model

Graph DBMS
Relational DBMS

Document store

Time Series DBMS

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

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

Website

bitnine.net/agensgraph

firebase.google.com/products/firestore

nsdb.io

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

Technical documentation

bitnine.net/documentation

firebase.google.com/docs/firestore

nsdb.io/Architecture

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

Developer

Bitnine Global Inc.

Google

Oracle

originally developed by Sleepycat, which was acquired by Oracle

Initial release

2016

2017

1994

Current release

2.1, December 2018

18.1.40, May 2020

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Apache Version 2.0

Open Source

commercial license 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

Java, Scala

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

Server operating systems

Linux
OS X
Windows

hosted

Linux
macOS

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Data scheme

depending on used data model

schema-free

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL-like query language

yes

SQL interfaced based on SQLite is available

APIs and other access methods

Cypher Query Language
JDBC

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

C
Java
JavaScript
Python

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

Java
Scala

.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

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

Triggers

yes, with Cloud Functions

yes

only for the SQL API

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

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