DBMS > Apache Drill vs. Faircom DB vs. GBase vs. Rockset

System Properties Comparison Apache Drill vs. Faircom DB vs. GBase vs. Rockset

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Editorial information provided by DB-Engines

Name

Description

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

Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A scalable, reliable search and analytics service in the cloud, built on RocksDB

Primary database model

Document store
Relational DBMS

Key-value store
Relational DBMS

Relational DBMS

Document store

Secondary database models

Relational DBMS
Search engine

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

Score	1.95
Rank	#127	Overall
	#23	Document stores
	#60	Relational DBMS

Score	0.20
Rank	#318	Overall
	#48	Key-value stores
	#141	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Website

drill.apache.org

www.faircom.com/products/faircom-db

www.gbase.cn

rockset.com

Technical documentation

drill.apache.org/docs

docs.faircom.com/docs/en/UUID-7446ae34-a1a7-c843-c894-d5322e395184.html

docs.rockset.com

Developer

Apache Software Foundation

FairCom Corporation

General Data Technology Co., Ltd.

Rockset

Initial release

2012

1979

2004

2019

Current release

1.20.3, January 2023

V12, November 2020

GBase 8a, GBase 8s, GBase 8c

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Restricted, free version available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

ANSI C, C++

C, Java, Python

C++

Server operating systems

Linux
OS X
Windows

AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows

easily portable to other OSs

Linux

hosted

Data scheme

schema-free

schema free, schema optional, schema required, partial schema,

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

yes

dynamic typing

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

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes, ANSI SQL with proprietary extensions

Standard with numerous extensions

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC

ADO.NET
C API
JDBC
ODBC

HTTP REST

Supported programming languages

C++

.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

.Net, JavaScript, C/C++

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

horizontal partitioning (by range, list and hash) and vertical partitioning

Automatic sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

Yes, tunable from durable to delayed durability to in-memory

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

Fine grained access rights according to SQL-standard with additional protections for files

yes

Access rights for users and organizations can be defined via Rockset console

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More resources

Recent citations in the news

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, TheServerSide.com

Analyse Kafka messages with SQL queries using Apache Drill
23 September 2019, Towards Data Science

Apache Drill Poised to Crack Tough Data Challenges
19 May 2015, Datanami

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

Apache Drill Eliminates ETL, Data Transformation for MapR Database
11 April 2016, The New Stack

provided by Google News

FairCom kicks off new era of database technology USA - English
10 November 2020, PR Newswire

provided by Google News

Rockset upgrades database to meet the needs of AI hybrid search – Blocks and Files
20 May 2024, Blocks & Files

Rockset Announces Native Support for Hybrid Search to Power AI Apps
17 May 2024, Datanami

Data Management News for the Week of May 17; Updates from Anomalo, DataStax, Rockset & More
16 May 2024, Solutions Review

Rockset launches native support for hybrid vector and text search to power AI apps
16 May 2024, SiliconANGLE News

Rockset Hybrid Search Release Sets New Course for Vector Databases
16 May 2024, Datanami

provided by Google News

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