DBMS > BigObject vs. Faircom DB vs. Rockset vs. Sequoiadb

System Properties Comparison BigObject vs. Faircom DB vs. Rockset vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

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

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

NewSQL database with distributed OLTP and SQL

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Key-value store
Relational DBMS

Document store

Document store
Relational DBMS

Secondary database models

Relational DBMS
Search engine

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

Score	0.19
Rank	#329	Overall
	#146	Relational DBMS

Score	0.29
Rank	#304	Overall
	#43	Key-value stores
	#136	Relational DBMS

Score	0.82
Rank	#212	Overall
	#36	Document stores

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Website

bigobject.io

www.faircom.com/products/faircom-db

rockset.com

www.sequoiadb.com

Technical documentation

docs.bigobject.io

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

docs.rockset.com

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

BigObject, Inc.

FairCom Corporation

Rockset

Sequoiadb Ltd.

Initial release

2015

1979

2019

2013

Current release

V12, November 2020

License

Commercial or Open Source

commercial

free community edition available

commercial

Restricted, free version available

commercial

Open Source

Server: AGPL; Client: Apache V2

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

ANSI C, C++

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

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

easily portable to other OSs

hosted

Linux

Data scheme

yes

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

schema-free

Typing

predefined data types such as float or date

yes

yes, ANSI SQL Types, JSON, typed binary structures

dynamic typing

yes

oid, date, timestamp, binary, regex

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.

ingestion from XML files supported

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like DML and DDL statements

yes, ANSI SQL with proprietary extensions

Read-only SQL queries, including JOINs

SQL-like query language

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

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

HTTP REST

proprietary protocol using JSON

Supported programming languages

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

Go
Java
JavaScript (Node.js)
Python

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

Lua

yes

.Net, JavaScript, C/C++

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

File partitioning, horizontal partitioning, sharding

Customizable business rules for table partitioning

Automatic sharding

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

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

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

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

Eventual Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

tunable from ACID to Eventually Consistent

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

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.

yes

User concepts

Access control

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

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

simple password-based access control

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