Splice Machine Blog

Webinar: Goodbye, Bottlenecks: How Scale-Out Hadoop and In-Memory Solve ETL  /  8.3.15 

The ETL (extract-transform-load) process was born out of necessity, and for decades, it has been the glue that holds together data sources and target applications. Anecdotally, it accounts for 70 percent of the effort in a data warehouse setup. But as data growth continues to soar, and as increased competition...

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Webinar: Run Operational Applications on Hadoop Using Splice Machine and Hortonworks  /  7.28.15 

As the collection of data proliferates, retailers are increasingly both overwhelmed by and interested in capturing the growing volumes to deliver greater value to their organizations. Whether the requirement is increasing revenue and margin, improving customer loyalty and consumer intimacy, or back-office...

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New Whitepaper: The Scale-Out Database Guide: When to use NoSQL vs. NewSQL  /  7.17.15 

To NoSQL or to NewSQL? The key to riding the wave of Big Data and enabling digital applications in real time is to select the right database that can support massive data growth without bursting IT budgets. The high cost of scaling up traditional relational databases, such as Oracle, IBM DB2 and MySQL,...

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Stuck in the Middle: The Future of Data Integration is No ETL  /  7.13.15 

The ETL (extract, transform and load) process was one born out of necessity, but it’s now a relic of the relational database era. Scale-out platforms like Hadoop and Spark provide the means to move beyond ETL, with lower cost data storage and processing power. Let’s look at how we got here and how...

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Splice Machine is now certified on MicroStrategy’s Analytics Platform  /  6.23.15 

We are excited to announce that we have officially achieved certification on the MicroStrategy Analytics Platform, the most powerful provider of data-driven analytics. Our partnersip will enable faster query times and real-time updates, powering operational analytics and reporting on up-to-the-second...

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