BitYota enables new unified Data collection and processing from 3rd party APIs, NoSQL databases and delivers streamlined Analytics
Poster: SySAdmin
Posted on October 10, 2014 at 10:07:01 AM
BitYota enables new unified Data collection and processing from 3rd party APIs, NoSQL databases and delivers streamlined Analytics
MOUNTAIN VIEW, Calif., Oct. 10, 2014 /PRNewswire/ -- Data Warehouse Service (DWS) provider BitYota today announced latest release of its flagship DWS for Big Data analytics. This update delivers the platform's data collection framework, an in-database processing pipeline for ELT (extract-load-transform), enhanced resource management and platform-specific improvements to further boost analytics performance. The new capabilities provide greater power, versatility and convenience to one of the industry's leading platforms for multi-structured data analytics.
"Some of the most valuable data available today comes from external sources such as 3(rd) party analytics APIs. With this new version of our Data Warehouse Service, BitYota offers users the ability to bring data in from numerous external sources, process it using their custom business rules and immediately begin interrogating data in multiple structures, using industry-standard SQL query language, all from within the DWS" said Dev Patel, CEO, BitYota.
The new DWS version also offers a range of features and upgrades that provide new performance and flexibility:
-- BitYota's data collection framework is providing a unified way to funnel
data from a wide variety of upstream 3rd party API sources like Mixpanel
and Flurry and NoSQL databases like MongoDB for real-time analysis.
BitYota is making its MongoDB and Mixpanel extract plugins with source
code available through its public Git Repository
(https://github.com/bityota-support/downloads). These are available for
use under the Apache 2.0 license, enabling users to modify code for
their use in their environment.
-- The ability to build a custom data pipeline using SQL within the DWS
that can be run on a schedule. By using standard SQL or user-defined
functions, customers can now leverage the true benefits of
Extract-Load-Transform (ELT) to extract and load the data in its raw
form and use the powerful BitYota massively parallel-processing (MPP)
engine for data transformations such as data quality checks,
aggregations on data arrival boundaries, creation of cubes, and other
data manipulation tasks directly in the DWS. Since no external data
pipelines need to be built, users are able to make business decisions on
insights much faster as data in available in minutes instead of hours,
while also reducing cost, complexity and operational steps.
-- Availability of compute and storage groups manageable by end users.
Building on BitYota's unique capability to separate and elastically
grow/shrink compute and storage nodes within a cluster, this feature
collects BitYota instances running on these nodes into discrete storage
or compute groups that can be assigned to individual users or business
roles. This eliminates resource contention between long and short
running jobs and enables better allocation of resources to improve
performance and ability to meet service-level agreements (SLAs)
-- Numerous performance improvements that enable faster loads, queries,
scan and join optimizations as well as improved aggregation and
exploration directly on semi-structured JSON. Our customers have seen
performance improvements in the range of 20% to 40%.
-- The BitYota DWS is now available in multiple new configurations. An
entry-level free node with up to a 1TB of storage and more powerful
Premium and Enterprise offerings that can scale up from 6TB to 100s of
TBs, creating multiple affordable price/performance points to scale your
DWS as your needs and usage grows.
"At CloudOn, we believe in a human-first design philosophy, the core of which lies in delivering delightful experiences," said Jay Zaveri, Chief Product Officer, CloudOn, a cloud storage provider enabling users to create, review and share files from any device. "Over 80 million documents have been created and edited on CloudOn and our ambition has always been to provide a gesture-first experience so we can push the boundaries on mobile content creation in ways that were never possible. In order to do so, we have to crunch data on 1 billion user actions (collected as raw JSON) every quarter that inform us on how we can fulfill this bold promise. BitYota serves as a cost-effective, high performance data warehouse that enables us to analyze raw session data from millions of users in seconds. A traditional analytics system just wouldn't work given the price and the flexibility we need. We load data into BitYota every hour, store, and explore this raw data. We look deep into user behavior with complete ease, and run ad-hoc queries, for example understanding churn and usage funnels, all using SQL over native JSON."
Availability
This release of BitYota's DWS is immediately available at no additional cost. For more about BitYota and its cloud-based DWS, visit http://www.bityota.com.
About BitYota
BitYota is a Data Warehouse Service in the Cloud for multi-structured data, designed from the ground up for fast, low-latency analytics on data from multiple upstream databases and applications. Founded in 2011 by executives and senior engineers with 35+ years of big data experience at Yahoo, Oracle, Veritas/Symantec, Informix, BMC and Microsoft, BitYota is headquartered in Mountain View, Calif. For more information, visit http://www.bityota.com.
SOURCE BitYota
BitYota
CONTACT: Mallory Snitker, 847-415-9300, msnitker@sspr.com
Web Site: http://www.bityota.com
MOUNTAIN VIEW, Calif., Oct. 10, 2014 /PRNewswire/ -- Data Warehouse Service (DWS) provider BitYota today announced latest release of its flagship DWS for Big Data analytics. This update delivers the platform's data collection framework, an in-database processing pipeline for ELT (extract-load-transform), enhanced resource management and platform-specific improvements to further boost analytics performance. The new capabilities provide greater power, versatility and convenience to one of the industry's leading platforms for multi-structured data analytics.
"Some of the most valuable data available today comes from external sources such as 3(rd) party analytics APIs. With this new version of our Data Warehouse Service, BitYota offers users the ability to bring data in from numerous external sources, process it using their custom business rules and immediately begin interrogating data in multiple structures, using industry-standard SQL query language, all from within the DWS" said Dev Patel, CEO, BitYota.
The new DWS version also offers a range of features and upgrades that provide new performance and flexibility:
-- BitYota's data collection framework is providing a unified way to funnel
data from a wide variety of upstream 3rd party API sources like Mixpanel
and Flurry and NoSQL databases like MongoDB for real-time analysis.
BitYota is making its MongoDB and Mixpanel extract plugins with source
code available through its public Git Repository
(https://github.com/bityota-support/downloads). These are available for
use under the Apache 2.0 license, enabling users to modify code for
their use in their environment.
-- The ability to build a custom data pipeline using SQL within the DWS
that can be run on a schedule. By using standard SQL or user-defined
functions, customers can now leverage the true benefits of
Extract-Load-Transform (ELT) to extract and load the data in its raw
form and use the powerful BitYota massively parallel-processing (MPP)
engine for data transformations such as data quality checks,
aggregations on data arrival boundaries, creation of cubes, and other
data manipulation tasks directly in the DWS. Since no external data
pipelines need to be built, users are able to make business decisions on
insights much faster as data in available in minutes instead of hours,
while also reducing cost, complexity and operational steps.
-- Availability of compute and storage groups manageable by end users.
Building on BitYota's unique capability to separate and elastically
grow/shrink compute and storage nodes within a cluster, this feature
collects BitYota instances running on these nodes into discrete storage
or compute groups that can be assigned to individual users or business
roles. This eliminates resource contention between long and short
running jobs and enables better allocation of resources to improve
performance and ability to meet service-level agreements (SLAs)
-- Numerous performance improvements that enable faster loads, queries,
scan and join optimizations as well as improved aggregation and
exploration directly on semi-structured JSON. Our customers have seen
performance improvements in the range of 20% to 40%.
-- The BitYota DWS is now available in multiple new configurations. An
entry-level free node with up to a 1TB of storage and more powerful
Premium and Enterprise offerings that can scale up from 6TB to 100s of
TBs, creating multiple affordable price/performance points to scale your
DWS as your needs and usage grows.
"At CloudOn, we believe in a human-first design philosophy, the core of which lies in delivering delightful experiences," said Jay Zaveri, Chief Product Officer, CloudOn, a cloud storage provider enabling users to create, review and share files from any device. "Over 80 million documents have been created and edited on CloudOn and our ambition has always been to provide a gesture-first experience so we can push the boundaries on mobile content creation in ways that were never possible. In order to do so, we have to crunch data on 1 billion user actions (collected as raw JSON) every quarter that inform us on how we can fulfill this bold promise. BitYota serves as a cost-effective, high performance data warehouse that enables us to analyze raw session data from millions of users in seconds. A traditional analytics system just wouldn't work given the price and the flexibility we need. We load data into BitYota every hour, store, and explore this raw data. We look deep into user behavior with complete ease, and run ad-hoc queries, for example understanding churn and usage funnels, all using SQL over native JSON."
Availability
This release of BitYota's DWS is immediately available at no additional cost. For more about BitYota and its cloud-based DWS, visit http://www.bityota.com.
About BitYota
BitYota is a Data Warehouse Service in the Cloud for multi-structured data, designed from the ground up for fast, low-latency analytics on data from multiple upstream databases and applications. Founded in 2011 by executives and senior engineers with 35+ years of big data experience at Yahoo, Oracle, Veritas/Symantec, Informix, BMC and Microsoft, BitYota is headquartered in Mountain View, Calif. For more information, visit http://www.bityota.com.
SOURCE BitYota
BitYota
CONTACT: Mallory Snitker, 847-415-9300, msnitker@sspr.com
Web Site: http://www.bityota.com