DBMS > Google Cloud Firestore vs. HEAVY.AI vs. JaguarDB vs. Snowflake vs. TerarkDB

System Properties Comparison Google Cloud Firestore vs. HEAVY.AI vs. JaguarDB vs. Snowflake vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

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.

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Performant, highly scalable DBMS for AI and IoT applications

Cloud-based data warehousing service for structured and semi-structured data

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Document store

Relational DBMS

Key-value store
Vector DBMS

Relational DBMS

Key-value store

Secondary database models

Spatial DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

firebase.google.com/products/firestore

github.com/heavyai/heavydb
www.heavy.ai

www.jaguardb.com

www.snowflake.com

github.com/bytedance/terarkdb

Technical documentation

firebase.google.com/docs/firestore

docs.heavy.ai

www.jaguardb.com/support.html

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Google

HEAVY.AI, Inc.

DataJaguar, Inc.

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

2017

2016

2015

2014

2016

Current release

5.10, January 2022

3.3 July 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; enterprise edition available

Open Source

GPL V3.0

commercial

restricted open source version 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

C++ and CUDA

C++

the server part. Clients available in other languages

C++

Server operating systems

hosted

Linux

hosted

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

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

JDBC
ODBC
Thrift
Vega

JDBC
ODBC

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

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

All languages supporting JDBC/ODBC/Thrift
Python

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

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

user defined functions

Triggers

yes, with Cloud Functions

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

Round robin

Sharding

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

none

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

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

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

User concepts

Access control

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

rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

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