DBMS > DolphinDB vs. Google Cloud Firestore vs. H2 vs. Oracle NoSQL

System Properties Comparison DolphinDB vs. Google Cloud Firestore vs. H2 vs. Oracle NoSQL

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Editorial information provided by DB-Engines

Name

Description

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

Primary database model

Time Series DBMS

Document store

Relational DBMS

Document store
Key-value store
Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	4.23
Rank	#82	Overall
	#6	Time Series DBMS

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	8.22
Rank	#50	Overall
	#32	Relational DBMS

Score	2.96
Rank	#103	Overall
	#18	Document stores
	#17	Key-value stores
	#52	Relational DBMS

Website

www.dolphindb.com

firebase.google.com/products/firestore

www.h2database.com

www.oracle.com/database/nosql/technologies/nosql

Technical documentation

docs.dolphindb.cn/en/help200/index.html

firebase.google.com/docs/firestore

www.h2database.com/html/main.html

docs.oracle.com/en/database/other-databases/nosql-database/index.html

Developer

DolphinDB, Inc

Google

Thomas Mueller

Oracle

Initial release

2018

2017

2005

2011

Current release

v2.00.4, January 2022

2.2.220, July 2023

23.3, December 2023

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

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

C++

Java

Server operating systems

Linux
Windows

hosted

All OS with a Java VM

Linux
Solaris SPARC/x86

Data scheme

yes

schema-free

yes

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

Typing

predefined data types such as float or date

yes

optional

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-like DML and DDL statements

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

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

JDBC
ODBC

RESTful HTTP API

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

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

Java

C
C#
Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

Java Stored Procedures and User-Defined Functions

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

With clustering: 2 database servers on different computers operate on identical copies of a database

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

configurable

ACID within a storage node (=shard)

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

off heap cache

User concepts

Access control

Administrators, Users, Groups

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

fine grained access rights according to SQL-standard

Access rights for users and roles

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More resources

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