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Bigdata Ingestion Software
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March 1, 2017

Wavefront

Wavefront is a hosted platform for ingesting, storing, visualizing and alerting on metric data. It is based on a stream processing approach invented at Google which allows engineers to manipulate metric data with unparalleled power. Wavefront makes analytics easy, yet powerful.  Our query language allows time series data to be manipulated in ways that have never been seen before.  The language is easy-to-understand, yet powerful enough to deal with high-dimensional data. Wavefront can ingest millions of data points per second. Leveraging an intuitive query language, you can manipulate data in real-time and deliver on actionable insights. This helps to [...]

21
 
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March 1, 2017

Syncsort

Syncsort provides enterprise software that allows organizations to collect, integrate, sort and distribute more data in less time, with fewer resources and lower costs. Syncsort software provides specialized solutions spanning “Big Iron to Big Data,” including next gen analytical platforms such as Hadoop, cloud, and Splunk.

Syncsort offers fast, secure, enterprise grade products to help the world’s leading organizations unleash the power of Big Data. With Syncsort, you can design your data applications once and deploy anywhere: from Windows, Unix & Linux to Hadoop; on premises or in the Cloud. Syncsort DMX-h was [...]

13.25
 
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March 1, 2017

DataTorrent

DataTorrent is the leader in real-time big data analytics. DataTorrent RTS provide high performing, fault tolerant unified architecture for both data in motion and data at rest. The engine provides a complete set of system services freeing the developer to focus on business logic. The platform is capable of processing billions of events per second and recovering from node outages with no data loss and no human intervention

DataTorrent RTS is proven in production environments to reduce time to market, development costs and operational expenditures for Fortune 100 and leading Internet companies. DataTorrent RTS provides [...]

21.5
 
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February 15, 2017

Apache Kafka

Apache Kafka is an open-source message broker project to provide a unified, high-throughput, low-latency platform for handling real-time data feeds. Kafka is a distributed, partitioned, replicated commit log service. It provides the functionality of a messaging system, but with a unique design. Kafka has a modern cluster-centric design that offers strong durability and fault-tolerance guarantees

Kafka is designed to allow a single cluster to serve as the central data backbone for a large organization. It can be elastically and transparently expanded without downtime. Data streams are partitioned and spread over a [...]

46.75
 
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November 1, 2016

Apache Storm

Apache Storm is a distributed realtime computation system. Storm makes it easy to reliably process unbounded streams of data, doing for realtime processing what Hadoop did for batch processing. Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more.Storm has many use cases: realtime analytics, online machine learning, continuous computation, distributed RPC, ETL, and more. Storm is fast: a benchmark clocked it at over a million tuples processed per second per node. It is scalable, fault-tolerant, guarantees your data will be processed, and is easy to set up and operate.

35
 
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November 1, 2016

Apache Samza

Apache Samza is a distributed stream processing framework. It uses Apache Kafka for messaging, and Apache Hadoop YARN to provide fault tolerance, processor isolation, security, and resource management. Unlike most low-level messaging system APIs, Samza provides a very simple callback-based “process message” API comparable to MapReduce. Samza manages snapshotting and restoration of a stream processor’s state. When the processor is restarted, Samza restores its state to a consistent snapshot. Samza is built to handle large amounts of state (many gigabytes per partition). Whenever a machine in the cluster fails, Samza works with YARN to transparently migrate [...]

15
 
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November 1, 2016

Apache Sqoop

Apache Sqoop is a tool designed for efficiently transferring bulk data between Apache Hadoop and structured datastores such as relational databases.Sqoop supports incremental loads of a single table or a free form SQL query, saved jobs which can be run multiple times to import updates made to a database since the last import. Imports can also be used to populate tables in Hive or HBase.Exports can be used to put data from Hadoop into a relational database. Sqoop got the name from sql+hadoop

Apache Sqoop

TrendingPAT Index™SORT       Apache Kafka Apache NIFI Apache [...]
11.25
 
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November 1, 2016

Apache Flume

Apache Flume is a distributed, reliable, and available service for efficiently collecting, aggregating, and moving large amounts of log data. It has a simple and flexible architecture based on streaming data flows. It is robust and fault tolerant with tunable reliability mechanisms and many failover and recovery mechanisms. It uses a simple extensible data model that allows for online analytic application.

Features include New in-memory channel that can spill to disk, A new dataset sink that use Kite API to write data to HDFS and HBase, Support for Elastic Search HTTP API in Elastic Search Sink and Much faster replay in [...]

13.5
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