DBMS > Apache Drill vs. Hive vs. Hypertable vs. Microsoft Azure Cosmos DB vs. SWC-DB

System Properties Comparison Apache Drill vs. Hive vs. Hypertable vs. Microsoft Azure Cosmos DB vs. SWC-DB

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

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

An open source BigTable implementation based on distributed file systems such as Hadoop

Globally distributed, horizontally scalable, multi-model database service

A high performance, scalable Wide Column DBMS

Primary database model

Document store
Relational DBMS

Relational DBMS

Wide column store

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Secondary database models

Spatial DBMS

Time Series DBMS

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

Score	2.02
Rank	#124	Overall
	#22	Document stores
	#59	Relational DBMS

Score	59.76
Rank	#18	Overall
	#12	Relational DBMS

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

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

drill.apache.org

hive.apache.org

azure.microsoft.com/services/cosmos-db

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

drill.apache.org/docs

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

learn.microsoft.com/azure/cosmos-db

Developer

Apache Software Foundation

initially developed by Facebook

Hypertable Inc.

Microsoft

Alex Kashirin

Initial release

2012

2009

2014

2020

Current release

1.20.3, January 2023

3.1.3, April 2022

0.9.8.11, March 2016

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2

Open Source

GNU version 3. Commercial license available

commercial

Open Source

GPL V3

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

Linux
OS X
Windows

an inofficial Windows port is available

hosted

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

restricted

only exact value or prefix value scans

yes

All properties auto-indexed by default

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
Thrift

C++ API
Thrift

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

Proprietary protocol
Thrift

Supported programming languages

C++

C++
Java
PHP
Python

C++
Java
Perl
PHP
Python
Ruby

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

C++

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions and integration of map-reduce

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

selectable replication factor on file system level

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

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

Depending on the underlying data source

User concepts

Access control

Depending on the underlying data source

Access rights for users, groups and roles

Access rights can be defined down to the item level

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