DBMS > Apache Drill vs. Google Cloud Firestore vs. jBASE vs. TerarkDB

System Properties Comparison Apache Drill vs. Google Cloud Firestore vs. jBASE vs. TerarkDB

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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 robust multi-value DBMS comprising development tools and middleware

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

Document store

Multivalue DBMS

Key-value store

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	6.63
Rank	#54	Overall
	#9	Document stores

Score	1.36
Rank	#157	Overall
	#3	Multivalue DBMS

Score	0.00
Rank	#385	Overall
	#61	Key-value stores

Website

drill.apache.org

firebase.google.com/products/firestore

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

github.com/bytedance/terarkdb

Technical documentation

drill.apache.org/docs

firebase.google.com/docs/firestore

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

Google

Rocket Software (formerly Zumasys)

ByteDance, originally Terark

Initial release

2012

2017

1991

2016

Current release

1.20.3, January 2023

5.7

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux
OS X
Windows

hosted

AIX
Linux
Windows

Data scheme

schema-free

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

Embedded SQL for jBASE in BASIC

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

C++ API
Java API

Supported programming languages

C++

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

.Net
Basic
Jabbascript
Java

C++
Java

Server-side scripts

Stored procedures

user defined functions

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

yes

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

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

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

yes

User concepts

Access control

Depending on the underlying data source

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

Access rights can be defined down to the item level

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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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