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Integrate your Google Sheets with your relational database or popular data warehouses like BigQuery, Redshift, or Snowflake.

Salesforce to MySQL integration is a breeze using DreamFactory's instant REST API creation capability. This quick tutorial shows how easy it is to integrate your Salesforce instance with a MySQL database to manage any number of data transactions you may want to push or pull between the systems.

In this episode of Michael Kaminksy's Databases Demystified, he explores: What does “consensus” mean and why is it important? Learn about the two-generals problem and what it teaches us about reaching consensus Learn about the main consensus algorithms in distributed databases: Raft & Paxos

In the first episode of Databases Demystified with Michael Kaminsky, we give a high-level overview of the most important concepts in databases. We start with a brief history of databases going from the invention of relational databases through present day and we talk about the differences between analytical and transactional databases, distributed and single-node databases, and in-memory vs on-disk databases We finish up talking briefly about SQL and what makes it special.

In this episode of Michael Kaminksy's Databases Demystified, we learn all about what a transaction is, and what ACID means. Learn why database constraints are important, and what the commands "begin" "commit" and "rollback" mean. We talk about atomicity, consistency, isolation, and durability and why transactions are so important.

Welcome to episode 5 of Michael Kaminksy's Databases Demystified, In this lesson we continue talking about transactions, but here we really get into the meat of transactions and talk about isolation levels and locks in much more detail.

Welcome to episode 6 of Michael Kaminsky's Databases Demystified. In this lesson, we introduce a fascinating and incredibly important topic: distributed databases. We discuss "nodes" and "clusters" and we cover the two major paradigms in distributed databases: big-compute databases and high-availability databases.

Episode 7 of Michael Kaminsky's Databases Demystified. Learn about new issues we face in distributed databases and all about the CAP theorem. We'll talk about leader and follower nodes, what happens when distributed databases lose connection with a node, and what CAP stands for: consistency, availability, and partition tolerance.

In Michael Kaminsky's third episode, we learn about the differences in row store vs column store database. This is a very important concept for understanding the difference between analytical and transactional databases, and we talk about the tradeoffs between using row and column stores for saving the data. Michael gets into the weeds and talks about disk blocks and the different types of queries that work well for row and column stores.