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What is IBM Cloud SQL Query?

Discover the advantages of serverless and interactive data querying with IBM Cloud Object Storage, which allows you to analyze data at its origin without the complexities of ETL processes, databases, or infrastructure management. With IBM Cloud SQL Query, powered by Apache Spark, you can perform high-speed, flexible analyses using SQL queries without needing to define ETL workflows or schemas. The intuitive query editor and REST API make it simple to conduct data analysis on your IBM Cloud Object Storage. Operating on a pay-per-query pricing model, you are charged solely for the data scanned, offering an economical approach that supports limitless queries. To maximize both cost savings and performance, you might want to consider compressing or partitioning your data. Additionally, IBM Cloud SQL Query guarantees high availability by executing queries across various computational resources situated in multiple locations. It supports an array of data formats, such as CSV, JSON, and Parquet, while also being compatible with standard ANSI SQL for query execution, thereby providing a flexible tool for data analysis. This functionality empowers organizations to make timely, data-driven decisions, enhancing their operational efficiency and strategic planning. Ultimately, the seamless integration of these features positions IBM Cloud SQL Query as an essential resource for modern data analysis.

What is Apache Parquet?

Parquet was created to offer the advantages of efficient and compressed columnar data formats across all initiatives within the Hadoop ecosystem. It takes into account complex nested data structures and utilizes the record shredding and assembly method described in the Dremel paper, which we consider to be a superior approach compared to just flattening nested namespaces. This format is specifically designed for maximum compression and encoding efficiency, with numerous projects demonstrating the substantial performance gains that can result from the effective use of these strategies. Parquet allows users to specify compression methods at the individual column level and is built to accommodate new encoding technologies as they arise and become accessible. Additionally, Parquet is crafted for widespread applicability, welcoming a broad spectrum of data processing frameworks within the Hadoop ecosystem without showing bias toward any particular one. By fostering interoperability and versatility, Parquet seeks to enable all users to fully harness its capabilities, enhancing their data processing tasks in various contexts. Ultimately, this commitment to inclusivity ensures that Parquet remains a valuable asset for a multitude of data-centric applications.

Media

Media

Integrations Supported

Autymate
Data Sentinel
IBM Cloud Object Storage
Lyftrondata

Integrations Supported

Autymate
Data Sentinel
3LC
APERIO DataWise
Amazon Data Firehose
Amazon SageMaker Data Wrangler
Apache DataFusion
Astera Dataprep
CSViewer
Gravity Data
GribStream
MLJAR Studio
Mage Sensitive Data Discovery
PuppyGraph
Querri
Semarchy xDI
Sliq
e6data

API Availability

Has API

API Availability

Pricing Information

$5.00/Terabyte-Month
Free Version
Free Trial Offered?

Pricing Information

Pricing not provided

Supported Platforms

SaaS
Windows
Mac
Linux

Supported Platforms

Windows
Mac
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars

Company Facts

Organization Name

IBM

Date Founded

1911

Company Location

United States

Company Website

www.ibm.com/cloud/sql-query

Company Facts

Organization Name

The Apache Software Foundation

Date Founded

1999

Company Location

United States

Company Website

parquet.apache.org

Categories and Features

Relational Database

ACID Compliance
Data Failure Recovery
Multi-Platform
Referential Integrity
SQL DDL Support
SQL DML Support
System Catalog
Unicode Support

Categories and Features

Columnar Databases

Not specified

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