DBMS > Cachelot.io vs. Fujitsu Enterprise Postgres vs. HBase vs. Sequoiadb

System Properties Comparison Cachelot.io vs. Fujitsu Enterprise Postgres vs. HBase vs. Sequoiadb

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Editorial information provided by DB-Engines

Name

Description

In-memory caching system

Enterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.

Wide-column store based on Apache Hadoop and on concepts of BigTable

NewSQL database with distributed OLTP and SQL

Primary database model

Key-value store

Relational DBMS

Wide column store

Document store
Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

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

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

cachelot.io

www.postgresql.fastware.com

hbase.apache.org

www.sequoiadb.com

Technical documentation

www.postgresql.fastware.com/product-manuals

hbase.apache.org/book.html

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

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Sequoiadb Ltd.

Initial release

2015

2008

2013

Current release

Fujitsu Enterprise Postgres 14, January 2022

2.3.4, January 2021

License

Commercial or Open Source

Open Source

Simplified BSD License

commercial

Open Source

Apache version 2

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java

C++

Server operating systems

FreeBSD
Linux
OS X

Linux
Windows

Linux
Unix
Windows

using Cygwin

Linux

Data scheme

schema-free

yes

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

Memcached protocol

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Java API
RESTful HTTP API
Thrift

proprietary protocol using JSON

Supported programming languages

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C#
C++
Groovy
Java
PHP
Python
Scala

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

yes

Coprocessors in Java

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

partitioning by range, list and by hash

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Immediate Consistency or Eventual Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

simple password-based access control

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
» more

Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
» more

Market metrics

Over 30 years experience in database technology. Over 20 years in Postgres development...
» more

Licensing and pricing models

Core based licensing
» more

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