DBMS > Fujitsu Enterprise Postgres vs. Google BigQuery vs. NCache vs. Prometheus vs. SwayDB

System Properties Comparison Fujitsu Enterprise Postgres vs. Google BigQuery vs. NCache vs. Prometheus vs. SwayDB

Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service with append-only tables

Open-Source and Enterprise in-memory Key-Value Store

Open-source Time Series DBMS and monitoring system

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Secondary database models

Document store
Spatial DBMS

Document store
Search engine

Using distributed Lucene

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

Score	0.31
Rank	#285	Overall
	#129	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Score	0.94
Rank	#195	Overall
	#29	Key-value stores

Score	8.42
Rank	#47	Overall
	#2	Time Series DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

www.postgresql.fastware.com

cloud.google.com/bigquery

www.alachisoft.com/ncache

prometheus.io

swaydb.simer.au

Technical documentation

www.postgresql.fastware.com/product-manuals

cloud.google.com/bigquery/docs

www.alachisoft.com/resources/docs

prometheus.io/docs

Developer

PostgreSQL Global Development Group, Fujitsu Australia Software Technology

Google

Alachisoft

Simer Plaha

Initial release

2010

2005

2015

2018

Current release

Fujitsu Enterprise Postgres 14, January 2022

5.3.3, April 2024

License

Commercial or Open Source

commercial

Open Source

Enterprise Edition available

Open Source

Apache 2.0

Open Source

GNU Affero GPL V3.0

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#, .NET, .NET Core, Java

Scala

Server operating systems

Linux
Windows

hosted

Linux
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

Numeric data only

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.

Import of XML data possible

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

APIs and other access methods

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

RESTful HTTP/JSON API

IDistributedCache
JCache
LINQ
Proprietary native API

RESTful HTTP/JSON API

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

Java
Kotlin
Scala

Server-side scripts

Stored procedures

user defined functions

in JavaScript

support for stored procedures with SQL-Server CLR

Triggers

yes

Notifications

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and by hash

none

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes, with selectable consistency level

yes

by Federation

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Since BigQuery is designed for querying data

optimistic locking and pessimistic locking

Atomic execution of operations

Concurrency

Support for concurrent manipulation of data

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

More information provided by the system vendor

Specific characteristics

100% compatible with community PostgreSQL
» more

NCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
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Competitive advantages

Built-in TDE and Data Masking security. In-Memory Columnar Index, and a high speed...
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NCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
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Typical application scenarios

Transactional payments applications, reporting and mixed workloads.
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NCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
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Key customers

Bank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
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Market metrics

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

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

Core based licensing
» more

NCache Open Source is free on an as-is basis without any support. NCache Enterprise...
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