DBMS > Blueflood vs. Google Cloud Bigtable vs. Hive vs. InfluxDB vs. Microsoft Azure Cosmos DB

System Properties Comparison Blueflood vs. Google Cloud Bigtable vs. Hive vs. InfluxDB vs. Microsoft Azure Cosmos DB

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.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

DBMS for storing time series, events and metrics

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Time Series DBMS

Key-value store
Wide column store

Relational DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

with GEO package

Spatial DBMS

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

Score	0.13
Rank	#346	Overall
	#33	Time Series DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

Score	24.39
Rank	#28	Overall
	#1	Time Series DBMS

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Website

blueflood.io

cloud.google.com/bigtable

hive.apache.org

www.influxdata.com/products/influxdb-overview

azure.microsoft.com/services/cosmos-db

Technical documentation

github.com/rax-maas/blueflood/wiki

cloud.google.com/bigtable/docs

cwiki.apache.org/confluence/display/Hive/Home

docs.influxdata.com/influxdb

learn.microsoft.com/azure/cosmos-db

Developer

Rackspace

Google

Apache Software Foundation

initially developed by Facebook

Microsoft

Initial release

2013

2015

2012

2013

2014

Current release

3.1.3, April 2022

2.7.6, April 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Open Source

Apache Version 2

Open Source

MIT-License; commercial enterprise version available

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

Server operating systems

Linux
OS X

hosted

All OS with a Java VM

Linux
OS X

through Homebrew

hosted

Data scheme

predefined scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

yes

JSON types

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 properties auto-indexed by default

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

HTTP REST

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

JDBC
ODBC
Thrift

HTTP API
JSON over UDP

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

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

C++
Java
PHP
Python

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on Cassandra

Sharding

in enterprise version only

Sharding

Implicit feature of the cloud service

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

selectable replication factor

in enterprise version only

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

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)

Eventual Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomic single-row operations

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

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

Depending on used storage engine

User concepts

Access control

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

Access rights for users, groups and roles

simple rights management via user accounts

Access rights can be defined down to the item level

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Key customers

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Market metrics

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Licensing and pricing models

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