Designed from the ground up as a native in-memory solution, ActivePivot’s processing is x200 times faster than disk-based RDBMSs.
This translates into the processing of big data at an accelerated speed with no latency. Data analysis that traditionally requires overnight batch processing is instead processed in real-time - bringing BI data analysis directly Into business operations.
By converging OLTP and OLAP data processing into a mixed-workload database, ActivePivot lets you run queries on dynamic data that gets refreshed frequently. It extracts and stores data in its native format, eliminating the need for data transformations and duplications. Then, when it detects new or modified data in the source system, it incrementally updates its cube and pushes changes to the front-end interface - whether ActiveUI, Excel, or any home-grown, MDX-compliant interface.
To support the simultaneous mix of queries and intense data updates, ActivePivot’s ‘Multiversion Concurrency Control’ feature holds several versions of the same data, so that one group of users can perform data analysis, while another group can performs real-time updates of the same data.
All data. Any dimension
Forget the restrictions imposed by
obsolete OLAP systems and the “curse of dimensionality.”
With ActivePivot you gain insight into the exact data you need - regardless of how it is stored or structured. Every column can be a dimension, so there’s absolutely no limit on your analysis criteria. Our customers use hundreds of dimensional queries without even stretching the full power of ActivePivot. Come to think of it - shouldn’t your analytical system comply with your needs, rather than the other way around?
'What-If' scenarios are run by modifying data directly within the analysis cube. Each user in your team can independently perform simulations and run queries with full privacy and with no impact on other users or operational data.
Data can be added or removed from the cube and drill-downs can be run on large data sets with results delivered instantly to each scenario query.
Root-cause analysis that goes back in time
With ActivePivot you can go back and analyze data snapshots within any historical time period to pinpoint a cause of a breach - even when this entails large data volumes with high-frequency data streams.
ActivePivot’s MDX (Multidimensional Expressions) engine supports the most demanding analytical queries by building a multidimensional view of aggregated data.
Using a column-based data store, each dimension requires only one additional column- so that complex analysis involving hundreds of dimensions is calculated on the fly.
The MDX engine also facilitates ActivePivot’s compatibility with multiple front end user interfaces - including Excel, Tableau, Spotfire, OBIEE, ActiveUI and others.
ActivePivot’s post processors offer the maximum flexibility for data aggregation and manipulation.
Defined using Java code, Post Processors are evaluated at query time for each requested aggregate and enable custom calculations as well as the computation of values from any external data resource.
Originally designed for multi-core hardware, ActivePivot has since evolved to take full advantage of NUMA (Non-Uniform Memory Access) hardware environments that use many cores - resulting in massive performance gains.
The ActiveViam Platform
The ActiveViam product family includes the following products:
An in-memory database combining transactional and analytical processing to handle the aggregation of ever-changing data.
A rule-based module with workflow and real-time alerting services for KPI management and monitoring.
An MDX-based data discovery interface with dashboards to enable real-time decisions.
A NoSQL database that offers best-in-class transfer rate, reliability and scalability and still runs on standard hardware.
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