Upsolver

Sisense is one of the leading #software providers in the highly competitive #businessintelligence and #analytics space. Seeking to expand the scope of its internal analytics, Sisense set out to build a data lake in the Amazon Web Services (AWS) cloud in order to more effectively store and analyze product usage data and following a recommendation from the AWS team, began looking into Upsolver’s #datalake platform. Read the full case study now: https://www.upsolver.com/case-studies/sisense-s3-data-lake

Have you heard the exciting #news? Amazon Web Services has announced the original Athena service has been upgraded to Athena 2! Read the full story to learn more about Athena 2:

Take a dive into our recent blog post to learn about individual elements that make up #datalake governance and security #bestpractice methods. You'll discover how they function together, and how the data is both governed and protected. Check it out now!

#happyholidays to our community!

Want to learn more about how Spark structured streaming and the Apache Spark streaming model compare? Read our latest blog post to learn more! #learneveryday #spark #apachespark

Did you know that #streamingdata analytics is expected to grow into a $38.6 billion market by 2025? We live in a world of #data: There’s more of it than ever before, in a ceaselessly expanding array of forms and locations. Take a dive into this recent article published by Sisense, where Upsolver's CEO & Co-founder Ori Rafael discusses how Upsolver, Amazon Web Services, and Sisense can be used together to deliver an end-to-end solution for streaming data analytics that is quick to set up, easy to operate without coding, and scales elastically using cloud computing/storage.

One of the most popular tools for working with #streamingdata is Apache Kafka. If you're facing the #dilemma when/if to use it, dive into our latest blog post, where we discuss the best scenarios for deploying Kafka.

BIG DAY at Upsolver! We released native ingestion connectors to Redshift and Snowflake, creating the first-ever truly open cloud lakehouse. Now, data-intensive enterprises can easily switch between data warehouses and data lake query engines, across multiple vendors. Get the full scoop! ... https://bwnews.pr/3jRhY5m See more

Are you using the #streaming approach for building your #softwaresystems? Take a dive into our latest #blogpost to learn how event sourcing and the concept of Command Query Responsibility Segregation (CQRS) can be helpful and beneficial when doing so

When it comes to #dataarchitecture, there are several approaches and principles pertaining to what a data warehouse should look like, what architecture should be used, etc. One of the options a data warehouse developer should consider is the type of the #schema they want to use. Dive into our latest blog to explore and compare two common options: The star schema and the snowflake schema!

Upsolver wishes all our Israeli friends a happy #newyear! Here’s to a healthy, happy, and cheerful year ahead for all

Calling all #dataengineers, #dataarchitects, #CTOs, #dataanalysts working on Amazon Web Services - we've got a workshop just for you! Join us and Amazon Web Services on October 27th to learn how to easily build a #datalakehouse on AWS. This hands-on virtual workshop will allow you to transform and aggregate streaming data with Upsolver and AWS Kinesis, and will provide the opportunity to analyze your data on Amazon Athena.... **Please note this event will be held in Hebrew** Grab your #virtual seat before space fills up! https://www.upsolver.com//webinar-aws-dev-day-build-lakeho

How does your data team analyze petabytes of data? When it comes to all the options out there, Amazon Athena and Amazon Redshift are two great services. So which one should you use? Check out our latest blog post to learn how their pricing compares through the use cases and scenarios presented:

I chose Upsolver because time-to-analytics over Amazon S3 is 20X faster compared to Spark. Our existing staff deployed a production-ready solution within one month, which eliminated the risk of not being able to replace IBM Netezza on schedule. Want to know how Upsolver provides Peer39 with a cloud-native, data stream processing platform with an easy to use UI that allows Peer39 to deploy a modernized data stack in the Cloud on time and under budget ? Read the full case study now:

Dive into the future of data infrastructure with our CEO & co-founder Ori Rafael in the inaugural post of The Cloud Lakehouse blog. Ori will re-examine warehouses and lakes throughout the series, pushing to rethink data platform architecture!

The Meet Group, a leading provider of interactive online dating solutions, was looking for a solution to integrate its #datapipelines and central data collection to drive better #realtime aggregate insights and analysis. Check out the full case study to learn how Upsolver developed a powerful and scalable #datalake that enables them to save time and innovate faster to meet business demands

Using #Splunk and searching for ways to cut costs? Find out how to reduce your #Splunk spending by 90% with Upsolver and #Amazon S3 in our latest blog post: