This is the first in a series of articles explaining the key highlights of the geospatial functions of IBM Cloud SQL Query. We will cover the Full Earth feature of the geospatial functions in this article—i.e., every topological and metric function operating on the Full Earth or the ellipsoidal Earth model.
IBM Cloud SQL Query lets you use standard SQL and Apache Spark SQL functions to query your structured and semi-structured data stored in Cloud Object Storage (COS). It’s a serverless solution that makes it easy to analyze lots of data in COS by pointing to the COS bucket that stores your data.
Geospatial data plays a crucial role in data forecasting, spatial analytics, and reporting, especially in the fields of logistics and finance. With IBM Cloud SQL Query, you can now run SQL queries on geospatial data on files stored as CSV, Parquet, or JSON in IBM Cloud Object Storage (COS) using IBM's geospatial toolkit.
Today, Db2 on Cloud already has excellent availability characteristics, with a 99.99% SLA and the ability to scale your database without app downtime, unlike other competitors in the market.
Over the Summer I learned that Python is top in the IEEE programming languages ranking. It is also my favorite language for quickly coding tools, web apps and analyzing data with notebooks (e.g., on IBM Data Science Experience). Did you know that IBM provides four (4) different Db2 drivers for Python? There is a driver with the native Db2 API, one that supports the official Python DBI (database interface), one for the popular SQLAlchemy Python SQL Toolkit, and for the Python-based Django Web Framework. In an older blog I showed you how to use SQLAlchemy with Db2. Today, I am going to demonstrate you how simple it is to create a SQL database-backed web app in the IBM Cloud, utilizing the native Db2 API.
Queryplex runs advanced analytics (SQL, Python, R, PySpark, etc) across many devices and data sources as though they are a single consolidated data repository. The technology can be used to erase data silos of multiple databases (e.g. Oracle, DB2, PostgreSQL, Netezza), or compute analytics across tens of thousands of distributed Internet of Things devices where data may be stored in smaller repositories (text files, Excel spreadsheets, Informix, MySQL). Queryplex let's you query many data sources at once with a single statement, whether they are large repositories, small devices, or any combination of them.
Easily provision IBM dashDB for Analytics and IBM dashDB for Transactions cloud offerings directly from the IBM Bluemix platform.
When you have an SQL database that deals with multiple users, there's a tough choice to make over how you set up and access your tables to provide security. One model that's growing in adoption is to give each user their own, separate schema, database or set of tables. This is called a multitenant architecture, or multitenancy. This post presents the pros/cons of multitenancy and shared tenancy.