DBMS > Apache Drill vs. Google BigQuery vs. Hypertable vs. SWC-DB vs. Transwarp ArgoDB

System Properties Comparison Apache Drill vs. Google BigQuery vs. Hypertable vs. SWC-DB vs. Transwarp ArgoDB

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

Large scale data warehouse service with append-only tables

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

A high performance, scalable Wide Column DBMS

Distributed Analytical Database to replace Hadoop+MPP hybrid architecture

Primary database model

Document store
Relational DBMS

Relational DBMS

Wide column store

Relational DBMS

Secondary database models

Time Series DBMS

Search engine

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	0.01
Rank	#378	Overall
	#13	Wide column stores

Score	0.04
Rank	#361	Overall
	#153	Relational DBMS

Website

drill.apache.org

cloud.google.com/bigquery

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

www.transwarp.cn/en/product/argodb

Technical documentation

drill.apache.org/docs

cloud.google.com/bigquery/docs

docs.transwarp.cn/#/documents-support/docs?category=ARGODB

Developer

Apache Software Foundation

Google

Hypertable Inc.

Alex Kashirin

Transwarp

Initial release

2012

2010

2009

2020

Current release

1.20.3, January 2023

0.9.8.11, March 2016

0.5, April 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

GNU version 3. Commercial license available

Open Source

GPL V3

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X
Windows

an inofficial Windows port is available

Linux

Data scheme

schema-free

yes

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

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

SQL-like query language

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

RESTful HTTP/JSON API

C++ API
Thrift

Proprietary protocol
Thrift

Supported programming languages

C++

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

C++
Java
Perl
PHP
Python
Ruby

C++

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Since BigQuery is designed for querying data

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

Google Cloud Identity & Access Management (IAM)

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