We are a team of experienced entrepreneurs & engineers focused on the application of technology in the Data Processing, Data Integration and Business Intelligence domains.
Our industry backgrounds include
Investment Banking, Insurance, ISP and Telecommunication industries.
- Architectural targets: Embrace market shift in data processing
field and deliver next generation ETL platform adaptiveETL which
is Hadoop & Big Data compliant, massively parallel, supports
conventional ETL architectures, Virtualizable, Cloud and Grid
deployable, Horizontally & Vertically scalable.
- Manageability targets: Simplify Data Processing & Data Integration
to a level where low skilled IT staff will be able to deliver IT
projects without trade-off in elegance, simplicity and most
importantly performance of the applications.
- Our philosophy: Deliver no-lock-in next generation ETL platform which requires no
ETL platform specific coding skills. A high productivity platform with
low TCO footprint. Platform which can be customized & extended without
constraints by implementing custom code where and how customer see fit.
The ability to deliver on such ambitious objectives comes from in
depth experience gained from the numerous Data Processing, Data
Warehousing & Data Integration projects that we have been part of.
Legacy ETL platforms in conjunction with conventional development &
design paradigms are unable to meet demands of modern Big Data,
Massive Throughput & Low latency data processing requirements.
Data Integration can typically be characterized as a set of large (in
numbers), highly coupled and moderately complex units of ETL
transformations/code. This translates as high complexity and high
TCO for the majority of Data Integration, Business Intelligence and
Data Processing projects.
Data Processing commonly faces performance issues, long load times,
SLA breaks and long processing windows as a consequence of not highly
parallel, batch oriented rather than real time (low latency) design
paradigms & thinking.
Business Intelligence end users often require much smaller query
latencies from the ones delivered.
Our Response - new generation adaptiveETL platform
We have created generic, Big Data compliant, adaptiveETL platform
which is simple to setup, deliver projects in. Platform which solves
performance & extensibility issues of legacy ETL platforms. Time to
market of project delivery is being measured in days rather than
months. Skills required for delivery are reduced to the basics of IT
We have delivered a new generation ETL adaptiveETL platform,
which eliminates performance issues even for volumes typical only of
Financial Exchanges, Time Series Analysis & Real Time Risk Valuations.
Desktop computers running our platform have more processing bandwidth
than server hardware with the state of the art (read complex and
expensive) ETL tools running on dozens of CPUs.
StreamHorizon, the new generation adaptiveETL platform supports out of
the box integration for OLAP and In-Memory platform integration.
However, the ability to rapidly load data into database further
simplifies the Business Intelligence stack by eliminating the need to
have MOLAP or other alternatives acting as query accelerators behind
their relational databases (aggregate tables or equivalents). The
reduction in complexity results in reduced implementation and hardware
costs while delivering highly maintainable and easy to support system.
The performance of our platform (throughput measured in millions of
records per second) allows database experts to index their databases
to an extent previously unimaginable (4+ indexes per single fact
table) while still having real time ETL processing in place.
By bringing together simplicity of implementation (by reducing
development to simple XML customization) and processing performance we
aim to make seismic shift in Data Processing & Data Integration IT