Upsolver SQL Serieswiggersventurebeat is a powerful language that can be used to help businesses manage their data in a variety of ways. In this article, we’re going to discuss some of the most common use cases for Upsolver. You’ll also learn how to get started with the Upsolver platform. And you’ll have the chance to listen to Wiggers’ VentureBeat, a podcast by the Upsolver team!
What is Upsolver?
Upsolver SQL Serieswiggersventurebeat is a cloud-native platform that abstracts the engineering complexity of data lake ingestion, storage, and ETL, empowering any data practitioner to build pipelines that deliver continuous analytics-ready data in days, not months.
The Upsolver SQL Serieswiggersventurebeat platform ingests stream, file and database data sources in real-time and transforms it into analytics-ready staging or live target tables. The solution is fully self-service, and runs on any SQL language.
Data Management Solutions
Unlike opaque “processing units” that many data management solutions use, Upsolver’s prices are straightforward to understand and tied to customer value, not vendor costs.
Engines
Upsolver SQL Serieswiggersventurebeat ingest and processing engines automatically store and manage data in the data lake using optimal partitioning, file formats, and small file compaction to optimize performance. Moreover, Upsolver’s hot-cold architecture keeps your data fresh without any manual intervention.
Upsolver SQL Serieswiggersventurebeat also offers a built-in decoupled state store that scales to billions of keys and milliseconds of read latency, letting your pipelines execute scalable stateful operations on a single key-value data store. Its unique index compression outperforms Spark’s native state store by storing at least 10X more data in a given RAM footprint.
How can Upsolver Help my Business?
Upsolver makes it incredibly simple to build a governed data lake and to manage, integrate and prepare streaming data for analysis. Define pipelines using only SQL on auto-generated schema-on-read and a simple visual IDE, then blend data from streaming and large-scale batch sources to create analytics-ready tables.
Upsolver ingests data from Apache Kafka, Amazon Kinesis, and operational databases into a centralized data hub that is continuously updated with strongly typed schema-on-read. This data is then mapped to tables in various analytics tools using a powerful SQL-based syntax that can mesh multiple data sources into a single table.
Cost of Maintenance
Upsolver helps customers get their data from the data lake to their analysis tools faster and with fewer costs than moving to dedicated database instances. The solution supports high-volume transactional use cases while minimizing the cost of maintenance by providing strong consistency guarantee over object storage, continuous lock-free compaction, and partitioning and compression of small files.
What are the Benefits of Upsolver?
Upsolver combines the power of cloud data lakes with affordability and simplicity. It lets users build data pipelines quickly without writing code or orchestrating jobs, leveraging SQL to declaratively specify transformations.
Upsolver also makes it easy to prepare data for query engines. It works with a range of query engines and data systems including Amazon Athena, Redshift Spectrum and Snowflake.
Amazon Athena
For example, Amazon Athena requires compaction, encryption, schema migration and partitioning. Upsolver removes these obstacles, making Athena and other queries faster than ever.
System Logs
Similarly, Upsolver makes it easy to prepare a wide range of data types and formats for streaming analytics in a data lake. This includes system logs, clickstreams, IoT sensor feeds, and more.
Streaming data processing is rapidly becoming the norm, transforming data lakes into central hubs that connect raw data to analytics systems from cloud data warehouses to machine learning systems and graph databases. Upsolver empowers data lakes to become a crucial component in every company’s data stack, providing keener insights and delivering game-changing customer-facing data products.
Conclusion:
Wiggers’ VentureBeat is a name you might recognize as it has a vested interest in the world’s most successful start up incubator, TechCrunch. The company has a bevy of journalists and techies on hand to keep tabs on the latest and greatest in the tech world. The newsroom chums have a knack for spotting the good stuff and the juiciest ones are usually in good hands. A lucky few are even lucky enough to be able to hang out in the office on their lunch breaks. They have a few of the biggest names in technology, as well as a few of the most interesting to boot. The company also boasts a small but mighty stable of investors.
