Periscope Data, the world’s leading analytics platform for data professionals, introduced the first phase of its next-generation analytics warehouse integration, Data Engine by Periscope Data, that will help data teams achieve faster query performance and data ingestion at scale for any kind of workload, regardless of concurrency, data volume or query complexity. Data Engine helps bypass the most challenging but important steps in the ETL process, allowing customers to optimize their workflow and remain agile.
Starting today, Data Engine offers Periscope Data users the flexibility to efficiently ingest and process data on either Snowflake or Redshift infrastructure depending on their workloads. With future advancements of the project slated to be released in the coming months, Periscope Data will add a series of other data storage and processing options to ensure the best technology is available to every data team, for any given workload. Data Engine is tailor-made for data-driven companies with complex pipelines or expanding data needs that require options to facilitate faster, more efficient queries.
“Every second matters when it comes to querying data – as companies scale and their data volumes grow, they will need to know that they have the best infrastructure, be it Snowflake, Redshift or other options, for that specific job,” said Tom O’Neill, CTO and Co-Founder of Periscope Data. “These fast-scaling companies shouldn’t be limited to only one kind of data warehouse – Data Engine gives them the flexibility to ingest, process and analyze data in the fastest way possible.”
Today, different warehouse options on the market offer specialized benefits for different use cases. For data teams with a wide range of use cases, this often means they are forced to deal with poor query performance for some portions of their data analysis in exchange for quicker processing in other areas. Alternatively, some companies take on the burden of running several tech stacks internally to leverage specialized benefits of multiple warehouses. Data Engine eliminates this predicament – it lets Periscope Data route the intensive queries to the best-equipped warehouses, ensuring maximum scalability for cross-functional teams while creating a single source of truth for all users.
“Deciding which data warehouse to turn to for processing and analysis was an arduous process in the past,” said Annie Flippo, Head of Data Science at ThinkNear. “We’re a company that has a wide variety of needs around our datasets and analytics workloads, with our queries ranging from small and straightforward to extremely large-scale and complex. Periscope’s Data Engine is going to make the whole analytics process much easier for us – we look forward to scaling by leveraging the strengths of multiple data warehousing technologies through Periscope Data.”
“Periscope Data provides a powerful way for data teams to connect all their data in one place and start building visualizations to answer questions,” said Snowflake VP of Alliances, Walter Aldana. “We’re really excited to see how Data Engine shines light on the power of Snowflake’s lightning-fast data warehouse and helps drive better data decisions for the world’s leading data teams.”