Ken Adams, Senior Business Intelligence Consultant at Key2 Consulting
By: Ken Adams
 
 

Introduction

Delta Lake is an open source storage layer that sits on top of cloud storage technology such as Azure Data Lake Storage or Amazon S3. The technology was introduced by Databricks in 2019, and all of the code is available here. Delta Lake is an extension of Spark and markets the fact that it brings ACID transactions to data lakes. This is a huge step forward for data engineers.

Data integrity on data lakes is a challenge today due to the fact that failed ETL jobs can cause partial data to be written or corrupted. With Delta Lake, you are able to guarantee a write operation either completes fully or not at all, and thus prevent corrupt data.
 

source: https://delta.io/


 

7 Key Functionalities of Delta Lake

 

  1. ACID Transactions
  2. As mentioned earlier, ACID transactions capability is a huge advancement for data lakes. Typically, a data lake has numerous data streams with users reading data from and writing data to the lake. Delta Lake stores a transaction log (DeltaLog) which tracks all commits made to a directory since the beginning of time. This prevents “dirty reads” by the users.
     

  3. Schema Enforcement
  4. Delta Lake allows you to specify your schema and enforce it. This prevents the insertion of bad records during data integration.
     

  5. Schema Evolution
  6. Data changes over time and thus data engineers need to be able to adjust a table schema. Delta Lake provides the ability to easily make those changes automatically without unwieldly DDL.
     

  7. Time Travel
  8. The DeltaLog allows users to return to an older version of the data. This rollback functionality means bad updates can be reverted, data can be audited, and older copies of the data can be accessed for experimentation. Users have the ability to query the data using an “as of” timestamp. See below for an example SQL query:

     

  9. Parquet
  10. Data in the Delta Lake is stored in Apache Parquet format. This provides for valuable compression and encoding schemes that are native to Parquet.
     

  11. Data Manipulation (DML)
  12. Delta Lake provides the ability to merge, update, and delete data sets. This allows data engineers to comply with the most stringent of data regulations, such as GDPR and CCPA. This can be done using various APIs like Scala, Java, and Python. The syntax can be fairly simple – deltaTable.delete(“delay < 0").  

  13. Metadata Management
  14. Delta Lake treats metadata no different than data. The power of Spark’s distributed engine makes metadata management efficient. This means petabyte size tables with millions of partitions and files can be handled with ease. The DeltaLog also allows users to review metadata about all of the changes that have been applied to the data.
     

Delta Lakes Pricing

The Delta Lake technology is open source and has no cost. The pricing would then depend on the data lake technology being used. In Azure, this would fall to the cost of blob versus Azure Data Lake Storage (ADLS). Blob storage is typically cheaper but might not perform as well as ADLS with larger volumes of data. ADLS also integrates Azure Active Directory (AD) while blob storage does not. Pricing for both can be found here and here.
 

In Closing

Anyone starting a data lake or having an existing data lake should certainly consider Delta Lake. It is easily layered on top of a data lake and provides ACID transactions, metadata handling, time travel, and simple data manipulation. Organizations that require data be updated or removed to comply with privacy laws such as GDPR, HIPAA, FERPA, et al. should seriously consider Delta Lake.
If you’re interested in reading more please see the following links:

https://delta.io/

Databricks Delta Lake

Diving Into Delta Lake: Unpacking The Transaction Log

Diving Into Delta Lake: Schema Enforcement & Evolution

 

Questions?

Thanks for reading. We hope you found this blog post to be useful. Do let us know if you have any questions or topic ideas related to BI, analytics, the cloud, machine learning, SQL Server, Star Wars, or anything else of the like that you’d like us to write about. Simply leave us a comment below, and we’ll see what we can do!
 

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Key2 Consulting is a data warehousing and business intelligence company located in Atlanta, Georgia. We create and deliver custom data warehouse solutions, business intelligence solutions, and custom applications.

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