Aster Solutions

Data warehousing is an extremely valuable asset for today's data-driven company. It's also really hard to get it right. Data modeling, loading, backups, and performance-tuning keep the warehousing team busy around the clock.

Unfortunately, common data warehouse tools and engines maintain the status quo by tying a talented team down in preserving the status quo in the face of data growth. The most important step of deriving business value and monetizing data is relegated to a wish list of, “when we have time…”. Outdated data warehouse architecture is often to blame.

Aster nCluster is an analytic database for a new class of "frontline" data warehousing used at data-driven companies across several industries. Frontline data warehouses provide high-performance access to a persistent, comprehensive, and up-to-the-minute record of the business’s frontline data, enabling them to collect, manage and monetize terabytes per day of new data.

In our experience, the obstacles to deriving value and monetizing data at the business frontlines are rooted in fundamental technical hurdles which Aster nCluster helps overcome:

  • Data loading performance
    • Loads are too slow to keep up with analysis needs
    • Loading limited to nightly batch windows
  • Data growth
    • Overwhelming volume forces you to sample data
    • Lack of DW capacity forces unwanted data expiration/archiving
    • Slow queries force data aggregates or summaries
  • Query performance
    • Queries take too long to finish or don't finish at all
    • Performance degrades as data increases and queries increase
  • Administration
    • Unscheduled system downtime
    • Tedious management of existing data warehouse
    • Constantly increasing temporary storage space and/or memory
  • Scaling
    • Too expensive to scale data warehouse
    • Too much planning and administration required to scale
Top Picks
Whitepaper: New MapReduce Whitepaper
Webcast: Bringing Big Data Analytics to the Enterprise - 11/12, with Merv Adrian
Webinar: Service Oriented 'Analytics' - 11/19, with James Kobelius