DBMS > Apache Kylin vs. Google Cloud Bigtable vs. MonetDB vs. NSDb vs. PieCloudDB

System Properties Comparison Apache Kylin vs. Google Cloud Bigtable vs. MonetDB vs. NSDb vs. PieCloudDB

Editorial information provided by DB-Engines

Name

Description

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

A relational database management system that stores data in columns

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A cloud-native analytic database platform with new technologoy for elastic MPP

Primary database model

Relational DBMS

Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	1.18
Rank	#172	Overall
	#79	Relational DBMS

Score	3.26
Rank	#92	Overall
	#13	Key-value stores
	#8	Wide column stores

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.25
Rank	#304	Overall
	#138	Relational DBMS

Website

kylin.apache.org

cloud.google.com/bigtable

www.monetdb.org

nsdb.io

www.openpie.com

Technical documentation

kylin.apache.org/docs

cloud.google.com/bigtable/docs

www.monetdb.org/Documentation

nsdb.io/Architecture

Developer

Apache Software Foundation, originally contributed from eBay Inc

Google

MonetDB BV

OpenPie

Initial release

2015

2004

2017

Current release

3.1.0, July 2020

Dec2023 (11.49), December 2023

2.1, January 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache Version 2.0

commercial

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

Java

Java, Scala

Server operating systems

Linux

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
macOS

hosted

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

yes

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

all fields are automatically indexed

yes

SQL

Support of SQL

ANSI SQL for queries (using Apache Calcite)

yes

SQL 2003 with some extensions

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

gRPC
HTTP REST
WebSocket

CLI Client
JDBC
ODBC

Supported programming languages

C#
C++
Go
Java
JavaScript (Node.js)
Python

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Java
Scala

Java
PL/SQL
Python
R

Server-side scripts

Stored procedures

yes, in SQL, C, R

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Internal replication in Colossus, and regional replication between two clusters in different zones

none

Source-replica replication available in experimental status

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

In-memory capabilities

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

User concepts

Access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

User Roles and pluggable authentication with full SQL Standard

More information provided by the system vendor

Specific characteristics

PieCloudDB, OpenPie's flagship product, is a cutting-edge cloud-native data warehouse....
» more

Competitive advantages

Extreme Elastic: PieCloudDB utilizes a cutting-edge eMPP cloud-native architecture...
» more

Typical application scenarios

PieCloudDB is ideal for Data mining applications that require extreme scalability...
» more

Key customers

Sail-Cloud China Shipbuilding Group Haizhou System Soochow Securities etc.,
» more

Licensing and pricing models

PieCloudDB Community Edition: Community License, Free Download, Self-Hosted Deployment；...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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