DBMS > Apache Drill vs. GigaSpaces vs. Microsoft Azure SQL Database vs. SAP SQL Anywhere vs. Snowflake

System Properties Comparison Apache Drill vs. GigaSpaces vs. Microsoft Azure SQL Database vs. SAP SQL Anywhere vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

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

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Database as a Service offering with high compatibility to Microsoft SQL Server

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

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

Primary database model

Document store
Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Graph DBMS
Search engine

Document store
Graph DBMS
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	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

drill.apache.org

www.gigaspaces.com

azure.microsoft.com/en-us/products/azure-sql/database

www.sap.com/products/technology-platform/sql-anywhere.html

www.snowflake.com

Technical documentation

drill.apache.org/docs

docs.gigaspaces.com/latest/landing.html

docs.microsoft.com/en-us/azure/azure-sql

help.sap.com/docs/SAP_SQL_Anywhere

docs.snowflake.net/manuals/index.html

Developer

Apache Software Foundation

Gigaspaces Technologies

Microsoft

SAP

formerly Sybase

Snowflake Computing Inc.

Initial release

2012

2000

2010

1992

2014

Current release

1.20.3, January 2023

15.5, September 2020

V12

17, July 2015

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

Apache Version 2; Commercial licenses 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, C++, .Net

C++

Server operating systems

Linux
OS X
Windows

Linux
macOS
Solaris
Windows

hosted

AIX
HP-UX
Linux
OS X
Solaris
Windows

hosted

Data scheme

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

SQL-99 for query and DML statements

yes

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

ADO.NET
JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

CLI Client
JDBC
ODBC

Supported programming languages

C++

.Net
C++
Java
Python
Scala

.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions

yes

Transact SQL

yes, in C/C++, Java, .Net or Perl

user defined functions

Triggers

yes, event driven architecture

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes, with always 3 replicas available

Source-replica replication

Database mirroring

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

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

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

Role-based access control

fine grained access rights according to SQL-standard

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

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