Databricks is an industry-leading data analytics platform which is a one-stop product for all data requirements. Databricks is made by the creators of Apache Spark, Delta Lake, ML Flow, and Koalas. It builds on these technologies to deliver a true lakehouse data architecture, making it a robust platform that is reliable, scalable, and fast. Databricks speeds up innovations by synthesizing storage, engineering, business operations, security, and data science.
Databricks is integrated with Microsoft Azure, Amazon Web Services, and Google Cloud Platform. This enables users to easily manage a colossal amount of data and to continuously train and deploy machine learning models for AI applications. The platform handles all analytic deployments, ranging from ETL to models training and deployment.
Databricks deciphers the complexities of processing data to empower data scientists, engineers, and analysts with a simple collaborative environment to run interactive and scheduled data analysis workloads. The program takes advantage of AI’s cost-effectivity, flexibility, and cloud storage.
Databricks Key Features
Some of Databricks key features include:
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Cloud-native: Works well on any prominent cloud provider.
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Data storage: Stores a broad range of data, including structured, unstructured, and streaming.
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Self-governance: Built-in governance and security controls.
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Flexibility: Flexible for small-scale jobs as well as running large-scale jobs like Big Data processing because it’s built from Spark and is specifically optimized for Cloud environments.
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Data science tools: Production-ready data tooling, from engineering to BI, AI, and ML.
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Familiar languages: While Databricks is Spark-based, it allows commonly used programming languages like R, SQL, Scala, and Python to be used.
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Team sharing workspaces: Creates an environment that provides interactive workspaces for collaboration, which allow multiple members to collaborate for data model creation, machine learning, and data extraction.
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Data source: Performs limitless Big Data analytics by connecting to Cloud providers AWS, Azure, and Google, as well as on-premises SQL servers, JSON and CSV.
Reviews from Real Users
Databricks stands out from its competitors for several reasons. Two striking features are its collaborative ability and its ability to streamline multiple programming languages.
PeerSpot users take note of the advantages of these features. A Chief Research Officer in consumer goods writes, “We work with multiple people on notebooks and it enables us to work collaboratively in an easy way without having to worry about the infrastructure. I think the solution is very intuitive, very easy to use. And that's what you pay for.”
A business intelligence coordinator in construction notes, “The capacity of use of the different types of coding is valuable. Databricks also has good performance because it is running in spark extra storage, meaning the performance and the capacity use different kinds of codes.”
An Associate Manager who works in consultancy mentions, “The technology that allows us to write scripts within the solution is extremely beneficial. If I was, for example, able to script in SQL, R, Scala, Apache Spark, or Python, I would be able to use my knowledge to make a script in this solution. It is very user-friendly and you can also process the records and validation point of view. The ability to migrate from one environment to another is useful.”
Data is the most abundant and precious resource in an enterprise. It comes in all forms and is complex to merge, relate and analyze. Data analytics extract meaning from that data for business gain or productivity, often sharing those insights through analytics dashboards or analytics reports.
With organizations generating billions of terabytes of data a year, big data analytics techniques are the only way to understand and uncover value from today’s scale of data.
The best big data analytics tools must be able to process both structured and unstructured data such as text, documents, emails and other data stored in enterprise information management systems. They go further than reporting on historic performance, enabling companies to prescribe better actions through predictive analytics. These data analysis tools are often referred to as advanced analytics solutions, such as OpenText™ Magellan Analytics Suite, and are quickly becoming the preferred choice for enterprise analytics.