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Removed numerous broken resources from README #11

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11 changes: 1 addition & 10 deletions README.md
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* [SeqPig](http://seqpig.sourceforge.net/) - Simple and scalable scripting for large sequencing data set(ex: bioinfomation) in Hadoop .
* [SigmoidAnalytics Spork](https://github.com/sigmoidanalytics/spork) - Pig on Apache Spark.
* [SNAP](https://github.com/snap-stanford/snap) - Stanford Network Analysis Platform is a general purpose, high performance system for analysis and manipulation of large networks.
* [spark-dataflow](https://github.com/cloudera/spark-dataflow) - allows users to execute dataflow pipelines with Spark.
* [SpatialHadoop](http://spatialhadoop.cs.umn.edu/) - SpatialHadoop is a MapReduce extension to Apache Hadoop designed specially to work with spatial data. .
* [Spring for Apache Hadoop](http://projects.spring.io/spring-hadoop/) - unified configuration model and easy to use APIs for using HDFS, MapReduce, Pig, and Hive.
* [SQLStream Blaze](http://www.sqlstream.com/blaze/) - stream processing platform.
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* [MapR-DB](http://content.dataversity.net/rs/wilshireconferences/images/MapR-DB_Product_Preview_for_NoSQL_Now.pdf) - fast, scalable, and enterprise-ready in-Hadoop database architected to manage big data.
* [Netflix Priam](https://github.com/Netflix/Priam) - Co-Process for backup/recovery, Token Management, and Centralized Configuration management for Cassandra.
* [OhmData C5](http://ohmdata.com/) - improved version of HBase.
* [Palantir AtlasDB](https://www.palantir.com/2014/06/atlasdb-transactions-for-distributed-key-value-stores-part-i/) - a massively scalable datastore and transactional layer that can be placed on top of any key-value store to give it ACID properties.
* [Sqrrl](http://sqrrl.com/product/sqrrl-enterprise/) - NoSQL databases on top of Apache Accumulo.
* [Stratio Cassandra](http://docs.stratio.com/modules/cassandra-lucene-index/development/) - Cassandra index functionality has been extended to provide near real time search such as ElasticSearch or Solr, including full text search capabilities and multivariable, geospatial and bitemporal search.
* [Tephra](https://github.com/continuuity/tephra) - Transactions for HBase.
* [Twitter Manhattan](https://blog.twitter.com/2014/manhattan-our-real-time-multi-tenant-distributed-database-for-twitter-scale) - real-time, multi-tenant distributed database for Twitter scale.
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* [NuoDB](http://www.nuodb.com/) - SQL/ACID compliant distributed database.
* [Oracle Database](http://www.oracle.com/us/corporate/features/database-12c/index.html) - object-relational database management system.
* [Oracle TimesTen in-Memory Database](http://www.oracle.com/technetwork/database/database-technologies/timesten/overview/index.html) - in-memory, relational database management system with persistence and recoverability.
* [Pivotal GemFire XD](http://gemfirexd.docs.gopivotal.com/latest/userguide/index.html?q=about_users_guide.html/) - Low-latency, in-memory, distributed SQL data store. Provides SQL interface to in-memory table data, persistable in HDFS.
* [SAP HANA](http://www.saphana.com/welcome) - is an in-memory, column-oriented, relational database management system.
* [Segment SQL](https://segment.com/redshift) - Track your customer data to Amazon Redshift.
* [SenseiDB](http://senseidb.com/) - distributed, realtime, semi-structured database.
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* [Amazon RedShift](http://aws.amazon.com/redshift/) - data warehouse service, based on PostgreSQL.
* [Apache Arrow](http://arrow.apache.org/) - Powering Columnar In-Memory Analytics.
* [C-Store](http://db.lcs.mit.edu/projects/cstore/) - column oriented DBMS.
* [Google BigQuery](http://research.google.com/pubs/pub36632.html) - framework for interactive analysis, implementation of Dremel.
* [Google Dremel](http://research.google.com/pubs/pub36632.html) - framework for interactive analysis, implementation of Dremel.
* [MonetDB](https://www.monetdb.org/) - column store database.
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* [Akiban](http://www.akiban.com/) - Touted as SQL database with object structured storage.
* [AMPLAB Shark](https://github.com/amplab/shark/) - data warehouse system for Spark.
* [Apache Drill](http://incubator.apache.org/drill/) - framework for interactive analysis, inspired by Dremel.
* [Apache HCatalog](http://hive.apache.org/docs/hcat_r0.5.0/) - table and storage management layer for Hadoop.
* [Apache Hive](http://hive.apache.org/) - SQL-like data warehouse system for Hadoop.
* [Apache Optiq](https://wiki.apache.org/incubator/OptiqProposal) - framework that allows efficient translation of queries involving heterogeneous and federated data.
* [Apache Phoenix](http://phoenix.incubator.apache.org/index.html) - SQL skin over HBase.
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* [Facebook PrestoDB](http://prestodb.io/) - distributed SQL query engine.
* [Hadapt](http://hadapt.com/) - a native implementation of SQL for the Apache Hadoop open-source project.
* [Hekaton](https://en.wikipedia.org/wiki/Hekaton_(database)) - Refer to lock-free architecture for SQL Server 2014.
* [JethroData](http://jethrodata.com/product-2/product/) - index-based SQL engine for Hadoop.
* [Metanautix Quest](https://metanautix.com/product/) - data compute engine.
* [Pivotal HAWQ](http://www.gopivotal.com/pivotal-products/data/pivotal-hd) - SQL-like data warehouse system for Hadoop.
* [RainstorDB](http://rainstor.com/products/rainstor-database/) - database for storing petabyte-scale volumes of structured and semi-structured data.
* [Spark Catalyst](https://github.com/apache/spark/tree/master/sql) - is a Query Optimization Framework for Spark and Shark.
* [SparkSQL](http://databricks.com/blog/2014/03/26/Spark-SQL-manipulating-structured-data-using-Spark.html) - Manipulating Structured Data Using Spark.
Expand All @@ -403,7 +395,6 @@ Data
* [Amazon Kinesis](http://aws.amazon.com/kinesis/) - real-time processing of streaming data at massive scale.
* [Amazon Snowball](https://aws.amazon.com/importexport/) - a petabyte-scale data transport solution that uses secure appliances to transfer large amounts of data into and out of AWS.
* [AMPLab SampleClean](http://sampleclean.org/) - scalable techniques for data cleaning and statistical inference on dirty data.
* [Apache BookKeeper](http://zookeeper.apache.org/bookkeeper/) - a distributed logging service called BookKeeper and a distributed publish/subscribe system built on top of BookKeeper called Hedwig.
* [Apache Chukwa](http://incubator.apache.org/chukwa/) - data collection system.
* [Apache Flume](http://flume.apache.org/) - service to manage large amount of log data.
* [Apache Samza](http://samza.incubator.apache.org/) - stream processing framework, based on Kafla and YARN.
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### Security

* [Apache Knox Gateway](http://knox.apache.org/) - single point of secure access for Hadoop clusters.
* [Apache Ranger](http://argus.incubator.apache.org/) - framework to enable, monitor and manage comprehensive data security across the Hadoop platform (formerly called Apache Argus).
* [Apache Sentry](http://incubator.apache.org/projects/sentry.html) - security module for data stored in Hadoop.
* [PacketPig](https://github.com/packetloop/packetpig) - Open Source Big Data Security Analytics.
* [Voltage SecureData](http://www.voltage.com/products/securedata-enterprise/) - data protection framework.
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* [Eventhub](https://github.com/Codecademy/EventHub) - open source event analytics platform.
* [HIPI Library](http://hipi.cs.virginia.edu/) - API for performing image processing tasks on Hadoop's MapReduce.
* [Hunk](http://www.splunk.com/download/hunk) - Splunk analytics for Hadoop.
* [Logit.io](https://logit.io/) - big data analyzer.
* [MADlib](http://madlib.net/community/) - data-processing library of an RDBMS to analyze data.
* [PivotalR](https://github.com/gopivotal/PivotalR) - R on Pivotal HD / HAWQ and PostgreSQL.
* [Qubole](http://www.qubole.com/) - auto-scaling Hadoop cluster, built-in data connectors.
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