Showing posts with label platform. Show all posts
Showing posts with label platform. Show all posts

Sunday, December 4, 2016

Hortonworks data Platform

Hortonworks data Platform


Hortonworks Pursues Open Source Path Analytical DBMS: HBase; although not a DBMS, Hive is Hortonworks option for SQL querying on top of Hadoop. In-memory DBMS: Although not a DBMS, Apache Spark supports in-memory analysis on top of Hadoop. Hadoop distributions: Hortonworks Data Platform (HDP) 2.0, HDP for Windows, Hortonworks Sandbox (free, single-node desktop software offering Hadoop tutorials). Stream-processing technology: Open-source stream-processing options on Hadoop include Storm. Hardware/software systems: Partner appliances, preconfigured hardware, or both available from HP, Teradata and others. Hortonworks is a massive contributor to the open-source Hadoop community focused on building it into a broadly capable data-management platform. Hortonworks sets itself apart from competitors Cloudera and MapR by eschewing proprietary components. Everything in the Hortonworks Data Platform (HDP) is freely available as open-source software. To its critics -- the aforementioned competitors -- Hortonworks pushes this open-source point to a fault, waiting to ship sought-after functionality until it is community sanctified and avoiding new (and perhaps technically better approaches) that are not entirely open source. Hortonworks is sticking with -- and trying to improve -- Hive, for example, while Cloudera promises better SQL-on-Hadoop performance with Impala, which is open source, technically, but best managed with proprietary Cloudera Manager software. In short, HDP is the conservative Hadoop distribution, and Hortonworks reportedly undercuts its competitors on support costs. Hortonworks makes the point that theres no threat of vendor lock-in with its distribution, and everything shipping has been thoroughly tested and proven. You wont get any surprises, but nor will you get anything ahead of the rest of the community in performance, ease of management, or functionality.

Hortonworks Pursues Open Source Path

Analytical DBMS: HBase; although not a DBMS, Hive is Hortonworks option for SQL querying on top of Hadoop.
In-memory DBMS: Although not a DBMS, Apache Spark supports in-memory analysis on top of Hadoop.
Hadoop distributions: Hortonworks Data Platform (HDP) 2.0, HDP for Windows, Hortonworks Sandbox (free, single-node desktop software offering Hadoop tutorials).
Stream-processing technology: Open-source stream-processing options on Hadoop include Storm.
Hardware/software systems: Partner appliances, preconfigured hardware, or both available from HP, Teradata and others.
Hortonworks is a massive contributor to the open-source Hadoop community focused on building it into a broadly capable data-management platform. Hortonworks sets itself apart from competitors Cloudera and MapR by eschewing proprietary components. Everything in the Hortonworks Data Platform (HDP) is freely available as open-source software.
To its critics -- the aforementioned competitors -- Hortonworks pushes this open-source point to a fault, waiting to ship sought-after functionality until it is community sanctified and avoiding new (and perhaps technically better approaches) that are not entirely open source. Hortonworks is sticking with -- and trying to improve -- Hive, for example, while Cloudera promises better SQL-on-Hadoop performance with Impala, which is open source, technically, but best managed with proprietary Cloudera Manager software.
In short, HDP is the conservative Hadoop distribution, and Hortonworks reportedly undercuts its competitors on support costs. Hortonworks makes the point that theres no threat of vendor lock-in with its distribution, and everything shipping has been thoroughly tested and proven. You wont get any surprises, but nor will you get anything ahead of the rest of the community in performance, ease of management, or functionality.

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Saturday, August 20, 2016

IBM Big Data Platform

IBM Big Data Platform


IBM takes a comprehensive approach Analytical DBMS: DB2, Netezza. In-memory DBMS: DB2 with BLU Acceleration, solidDB. Hadoop distribution: InfoSphere BigInsights. Stream-processing technology: InfoSphere Streams. Hardware/software systems: PureData System For Operational Analytics (DB2), IBM PureData System for Analytics (Netezza); PureData System for Hadoop (BigInsights). IBM has the broadest data-management portfolio in the industry, hands down. In addition to offering all the platforms mentioned above, as well as mainframes, IBM has a bevy of data-integration, data-cleansing, and data-quality software options to help capture and clean data. It also has plenty of business intelligence and analytics offerings, including Cognos, SPSS, text- and unstructured-data mining options, and IBM-developed tools for Hadoop including Big Sheets and BigSQL. IBM is also building out its SaaS portfolio and cloud infrastructure, with the $2 billion SoftLayer acquisition being a tangible example of the cloud commitment. Although IBM has plenty of products and services, its not a product-oriented provider of technology. IBM leads with its deep integration and consulting expertise in a consultative approach focused on building business-differentiating solutions that might incorporate multiple products. The upside is that its not a cookie-cutter, one-size-fits-all approach, but competitors say beware of open-ended commitments and steep, ongoing consulting fees. Those choosing IBM expect an effective strategic approach that leads to significant business results. Its up to you to make sure you get what you pay for.

IBM takes a comprehensive approach

Analytical DBMS: DB2, Netezza.
In-memory DBMS: DB2 with BLU Acceleration, solidDB.
Hadoop distribution: InfoSphere BigInsights.
Stream-processing technology: InfoSphere Streams.
Hardware/software systems: PureData System For Operational Analytics (DB2), IBM PureData System for Analytics (Netezza); PureData System for Hadoop (BigInsights).
IBM has the broadest data-management portfolio in the industry, hands down. In addition to offering all the platforms mentioned above, as well as mainframes, IBM has a bevy of data-integration, data-cleansing, and data-quality software options to help capture and clean data. It also has plenty of business intelligence and analytics offerings, including Cognos, SPSS, text- and unstructured-data mining options, and IBM-developed tools for Hadoop including Big Sheets and BigSQL. IBM is also building out its SaaS portfolio and cloud infrastructure, with the $2 billion SoftLayer acquisition being a tangible example of the cloud commitment.
Although IBM has plenty of products and services, its not a product-oriented provider of technology. IBM leads with its deep integration and consulting expertise in a consultative approach focused on building business-differentiating "solutions" that might incorporate multiple products. The upside is that its not a cookie-cutter, one-size-fits-all approach, but competitors say beware of open-ended commitments and steep, ongoing consulting fees. Those choosing IBM expect an effective strategic approach that leads to significant business results. Its up to you to make sure you get what you pay for.

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