DBMS > Google BigQuery vs. HugeGraph vs. Hypertable vs. Snowflake

System Properties Comparison Google BigQuery vs. HugeGraph vs. Hypertable vs. Snowflake

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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

Large scale data warehouse service with append-only tables

A fast-speed and highly-scalable Graph DBMS

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

Cloud-based data warehousing service for structured and semi-structured data

Primary database model

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

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	0.17
Rank	#335	Overall
	#31	Graph DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

cloud.google.com/bigquery

github.com/hugegraph
hugegraph.apache.org

www.snowflake.com

Technical documentation

cloud.google.com/bigquery/docs

hugegraph.apache.org/docs

docs.snowflake.net/manuals/index.html

Developer

Google

Baidu

Hypertable Inc.

Snowflake Computing Inc.

Initial release

2010

2018

2009

2014

Current release

0.9

0.9.8.11, March 2016

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GNU version 3. Commercial license available

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

Java

C++

Server operating systems

hosted

Linux
macOS
Unix

Linux
OS X
Windows

an inofficial Windows port is available

hosted

Data scheme

yes

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

also supports composite index and range index

restricted

only exact value or prefix value scans

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP/JSON API

Java API
RESTful HTTP API
TinkerPop Gremlin

C++ API
Thrift

CLI Client
JDBC
ODBC

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Groovy
Java
Python

C++
Java
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

in JavaScript

asynchronous Gremlin script jobs

user defined functions

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

yes

depending on used storage backend, e.g. Cassandra and HBase

Sharding

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on used storage backend, e.g. Cassandra and HBase

selectable replication factor on file system level

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

via hugegraph-spark

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

edges in graph

yes

Transaction concepts

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

Since BigQuery is designed for querying data

ACID

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

User concepts

Access control

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

Google Cloud Identity & Access Management (IAM)

Users, roles and permissions

Users with fine-grained authorization concept, user roles and pluggable authentication

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