Databricks

Databricks is a unified, open analytics platform that enables the building, deployment, sharing, and maintenance of enterprise-grade data, analytics, and AI solutions at scale. The Databricks Data Intelligence Platform integrates with cloud storage and security in your cloud account and manages and deploys cloud infrastructure on your behalf.

Databricks uses generative AI with the data lakehouse to understand the unique semantics of your data, automatically optimize performance, and manage infrastructure to match your business needs. Natural language processing learns your business’s language, so you can search and discover data by asking a question in your own words.

Databricks provides tools that help you connect your sources of data to one platform to process, store, share, analyze, model, and monetize datasets with solutions from BI to generative AI. The Databricks workspace provides a unified interface and tools for most data tasks, including data processing scheduling and management, generating dashboards and visualizations, managing security, governance, high availability, and disaster recovery, data discovery, annotation, and exploration, machine learning modeling, tracking, and model serving, and generative AI solutions.

Databricks Features

• Open Analytics Platform: Databricks is a unified, open analytics platform for building, deploying, sharing, and maintaining enterprise-grade data, analytics, and AI solutions at scale.

• Data Intelligence Platform: The Databricks Data Intelligence Platform integrates with cloud storage and security in your cloud account, and manages and deploys cloud infrastructure on your behalf.

• Generative AI with Data Lakehouse: Databricks uses generative AI with the data lakehouse to understand the unique semantics of your data, automatically optimize performance, and manage infrastructure to match your business needs.

• Natural Language Processing: Natural language processing learns your business’s language, so you can search and discover data by asking a question in your own words.

• Data Processing Scheduling and Management: Databricks provides tools for data processing scheduling and management, particularly ETL.

• Dashboards and Visualizations: Databricks allow for generating dashboards and visualizations.

• Data Discovery, Annotation, and Exploration: Databricks provide tools for data discovery, annotation, and exploration.

• Machine Learning Modeling, Tracking, and Model Serving: Databricks provides tools for machine learning modeling, tracking, and model serving.

Databricks Pricing

• Free Plan
• Jobs: $0.07 per DBU
• Delta Live Tables: $0.02 per DBU
• Databricks SQL: $0.22 per DBU
• All-purpose compute for all interactive workloads: $0.40 per DBU
• Serverless Real-time interphase: $0.07 per DBU

Databricks Usages

• Building an Enterprise Data Lakehouse: Databricks can be used to build an enterprise data lakehouse. This allows organizations to store all their structured and unstructured data in one place for analytics.

• ETL and Data Engineering: Databricks provides tools for Extract, Transform, Load (ETL), and data engineering. This helps in processing large amounts of data and preparing it for analysis.

• Machine Learning, AI, and Data Science: Databricks can be used for machine learning, AI, and data science. It provides tools for machine learning modeling, tracking, and model serving.

• Data Warehousing, Analytics, and BI: Databricks can be used for data warehousing, analytics, and Business Intelligence (BI). It provides tools for generating dashboards and visualizations.

• Data Governance and Secure Data Sharing: Databricks provide tools for managing security, governance, high availability, and disaster recovery. This ensures that your data is secure and well-governed.

• DevOps, CI/CD, and Task Orchestration: Databricks can be used for DevOps, Continuous Integration/Continuous Deployment (CI/CD), and task orchestration. This helps in automating and managing the deployment of your data applications.

• Real-time and Streaming Analytics: Databricks can be used for real-time and streaming analytics. This allows you to analyze and make decisions based on real-time data.

Databricks Competitors

• Snowflake Computing: Snowflake provides a cloud-based data warehousing platform that competes with Databricks in the realm of data analytics and processing. Snowflake focuses on enabling organizations to store and analyze large volumes of data efficiently.

• Cloudera: Cloudera offers a platform for data management and analytics that competes with Databricks. Cloudera's platform includes tools for data ingestion, processing, analysis, and visualization, catering to enterprises with big data needs.

• Amazon Web Services (AWS) - Amazon EMR: AWS offers Amazon EMR (Elastic MapReduce), enabling users to process vast data volumes using open-source frameworks like Apache Spark and Apache Hadoop. Though not a direct rival to Databricks, it provides comparable data processing and analytics capabilities in the cloud.

Databricks Launch and Funding

Databricks was launched in 2013. Databricks has raised a total of $4.2 billion in funding over 12 rounds. Their latest funding was raised on Sep 14, 2023, from a Series I round. Databricks was founded by Ali Ghodsi, Andy Konwinski, Ion Stoica, Patrick Wendell, Reynold Xin, Matei Zaharia, and Arsalan Tavakoli. The current CEO of Databricks is Ali Ghodsi.

Databricks Limitations

• Limited Full SQL Experience: Databricks leverages the Delta Lakehouse paradigm, offering core BI functionalities but doesn’t provide a full traditional BI data warehouse experience.

• Limited T-SQL Experience: Databricks doesn’t provide a full T-SQL experience.