DBMS > Apache Drill vs. H2 vs. Snowflake vs. Transwarp Hippo

System Properties Comparison Apache Drill vs. H2 vs. Snowflake vs. Transwarp Hippo

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Editorial information provided by DB-Engines

Name

Description

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

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

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

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

Primary database model

Document store
Relational DBMS

Relational DBMS

Vector DBMS

Secondary database models

Spatial 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	8.33
Rank	#46	Overall
	#30	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.05
Rank	#386	Overall
	#15	Vector DBMS

Website

drill.apache.org

www.h2database.com

www.snowflake.com

www.transwarp.cn/en/subproduct/hippo

Technical documentation

drill.apache.org/docs

www.h2database.com/html/main.html

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Thomas Mueller

Snowflake Computing Inc.

Initial release

2012

2005

2014

2023

Current release

1.20.3, January 2023

2.2.220, July 2023

1.0, May 2023

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

dual-licence (Mozilla public license, Eclipse public license)

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

Linux
OS X
Windows

All OS with a Java VM

hosted

Linux
macOS

Data scheme

schema-free

yes

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

Typing

predefined data types such as float or date

yes

Vector, Numeric and String

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

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC

CLI Client
JDBC
ODBC

RESTful HTTP API

Supported programming languages

C++

Java

JavaScript (Node.js)
Python

C++
Java
Python

Server-side scripts

Stored procedures

user defined functions

Java Stored Procedures and User-Defined Functions

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

With clustering: 2 database servers on different computers operate on identical copies of a database

yes

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

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

yes

User concepts

Access control

Depending on the underlying data source

fine grained access rights according to SQL-standard

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

Role based access control and fine grained access rights

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