DBMS > Blueflood vs. Google Cloud Bigtable vs. Lovefield vs. MonetDB

System Properties Comparison Blueflood vs. Google Cloud Bigtable vs. Lovefield vs. MonetDB

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Editorial information provided by DB-Engines

Name

Description

Scalable TimeSeries DBMS based on Cassandra

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

Embeddable relational database for web apps written in pure JavaScript

A relational database management system that stores data in columns

Primary database model

Time Series DBMS

Key-value store
Wide column store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.06
Rank	#353	Overall
	#34	Time Series DBMS

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

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Website

blueflood.io

cloud.google.com/bigtable

google.github.io/lovefield

www.monetdb.org

Technical documentation

github.com/rax-maas/blueflood/wiki

cloud.google.com/bigtable/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

www.monetdb.org/Documentation

Developer

Rackspace

Google

MonetDB BV

Initial release

2013

2015

2014

2004

Current release

2.1.12, February 2017

Dec2023 (11.49), December 2023

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache 2.0

Open Source

Mozilla Public License 2.0

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

Java

JavaScript

Server operating systems

Linux
OS X

hosted

server-less, requires a JavaScript environment (browser, Node.js)

tested with Chrome, Firefox, IE, Safari

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

predefined scheme

schema-free

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

yes

SQL 2003 with some extensions

APIs and other access methods

HTTP REST

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Supported programming languages

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

JavaScript

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

Server-side scripts

Stored procedures

yes, in SQL, C, R

Triggers

Using read-only observers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

none

Sharding via remote tables

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on Cassandra

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

none

Source-replica replication available in experimental status

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

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

yes, by using IndexedDB or the cloud service Firebase Realtime Database

yes

In-memory capabilities

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

yes

using MemoryDB

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

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