DBMS > DolphinDB vs. Google Cloud Firestore vs. Hyprcubd vs. Ingres vs. XTDB

System Properties Comparison DolphinDB vs. Google Cloud Firestore vs. Hyprcubd vs. Ingres vs. XTDB

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

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.

Serverless Time Series DBMS

Well established RDBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Secondary database models

Relational DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	4.11
Rank	#81	Overall
	#44	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

www.dolphindb.com

firebase.google.com/products/firestore

hyprcubd.com (offline)

www.actian.com/databases/ingres

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

firebase.google.com/docs/firestore

docs.actian.com/ingres

www.xtdb.com/docs

Developer

DolphinDB, Inc

Google

Hyprcubd, Inc.

Actian Corporation

Juxt Ltd.

Initial release

2018

2017

1974

originally developed at University Berkely in early 1970s

2019

Current release

v2.00.4, January 2022

11.2, May 2022

1.19, September 2021

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

MIT License

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++

Clojure

Server operating systems

Linux
Windows

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

yes

yes, extensible-data-notation format

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

limited SQL, making use of Apache Calcite

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

gRPC (https)

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

HTTP REST
JDBC

Supported programming languages

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

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

Clojure
Java

Server-side scripts

Stored procedures

yes

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Ingres Replicator

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

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.

token access

fine grained access rights according to SQL-standard

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Related products and services

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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