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.”
GoodData provides cloud-based big data solutions to companies in any industry. GoodData's platform is a scalable, reliable and secure method of analyzing large data sets. It is specifically useful for companies seeking to gain insights into marketing, sales and customer service performance. GoodData's platform works with any data source and is able to load, store, analyze, visualize and share data sets. This business intelligence (BI) platform is able to access existing data from any source including SaaS, on premise, structured, and unstructured. It allows companies to monitor and manage multiple load processes from its data integration service console. GoodData's big data analysis uses Multidimensional Analytics Query Language (MAQL) and the Extensible Analytics Engine. The combination of these two features results in enhanced multi-level caching, increased performance and the option to include advanced metrics. The platform's data reporting and visualization features are user-friendly, customizable and are cross-platform compatible. GoodData improves collaboration among teams with advanced exporting and sharing capabilities via branded dashboards and offers 24/7 customer support. GoodData's platform has been implemented by many enterprises to improve and optimize services. Switchfly, a company that provides technology solutions aimed at increasing customer engagement, needed a big data platform that was able to efficiently analyze over 60 billion customer impressions made each year. After implementing GoodData's platform, Switchfly was able to provide their clients with relevant insights into customer behavior and accurately measure market impact. GoodData is just one of many SaaS business intelligence products reviewed in our SmartAdvisor; click the link to see more solutions.