hbase: All content tagged as hbase in NoSQL databases and polyglot persistence
The list of releases I wanted to post about has been growing fast these last couple of weeks, so instead of waiting leaving it to Here it is (in no particular order1):
- (Jan.2nd) Cassandra 1.2 — announcement on DataStax’s blog. I’m currently learning and working on a post looking at what’s new in Cassandra 1.2.
- (Jan.10th) Apache Pig 0.10.1 — Hortonworks wrote about it
- (Jan.10th) DataStax Community Edition 1.2 and OpsCenter 2.1.3 — DataStax announcement
- (Jan.10th) CouchDB 1.0.4, 1.1.2, and 1.2.1 — releases fixing some security vulnerabilities
(Jan.11th) MongoDB 2.3.2 unstable — announcement. This dev release includes support for full text indexing. For more details you can check:
- MongoDB Full Text Search Explained and MongoDB Text Search Tutorial
- Full text search in MongoDB: details about supported languages and queries
- Indexing a Markdown blog using MongoDB full text indexing
- Short demo of MongoDB text search and hashed shard keys
- (Jan.12th) Apache HBase 0.94.4 — announcement and release notes
- (Jan.14th) Apache Hive 0.10.0: Hortonworks’s post about it
- (Jan.15th) Hortonworks Data Platform 1.2 featuring Apache Amabari — official PR announcement
- (Jan.16th) Redis 2.6.9 — release notes
- (Jan.16th) HyperDex 1.0RC1 — no docs
- (Jan.16th) Klout’s Brickhouse — announcement:
[…] an open source project extending Hadoop and Hive with a collection of useful user-defined-functions. Its aim is to make the Hive Big Data developer more productive, and to enable scalable and robust dataflows.
I’ve tried to order it chronologically, but most probably I’ve failed. ↩
Original title and link: 11 Interesting Releases From the First Weeks of January ( ©myNoSQL)
A three part article from Hortonworks showing how Pig can be used with MongoDB, HBase, and Cassandra:
Pig has emerged as the ‘duct tape’ of Big Data, enabling you to send data between distributed systems in a few lines of code. In this series, we’re going to show you how to use Hadoop and Pig to connect different distributed systems, to enable you to process data from wherever and to wherever you like.
- Part 1: Pig, MongoDB and Node.js
- Part 2: Pig, HBase, JRuby and Sinatra
- Part 3: TF-IDF Topics with Cassandra, Python Streaming and Flask
Original title and link: Pig the Big Data Duct Tape: Examples for MongoDB, HBase, and Cassandra ( ©myNoSQL)
It’s unfortunate that the post focuses mostly on the usage of Spring and RabitMQ and the slidedeck doesn’t dive deeper into the architecture, data flows, and data stores, but the diagrams below should give you an idea of this truly polyglot persistentency architecture:
The slide deck presenting architecture principles and numbers about the platform after the break.
Just found slideck (embedded below) describing the data workflow at Klout. Their architecture includes many interesting pieces combining both NoSQL and relational databases with Hadoop and Hive and Pig and traditional BI. Even Excel gets a mention in the slides:
- Pig and Hive
- Elastic Search
Hortonworks has announced the 1.0 release of the Hortonworks Data Platform prior to the Hadoop Summit 2012 together with a lot of supporting quotes from companies like Attunity, Dataguise, Datameer, Karmasphere, Kognitio, MarkLogic, Microsoft, NetApp, StackIQ, Syncsort, Talend, 10gen, Teradata, and VMware.
Some info points:
Hortonworks Data Platform is a platform meant to simplify the installation, integration, management, and use of Apache Hadoop
- HDP 1.0 is based on Apache Hadoop 1.0
- Apache Ambari is used for installation and provisioning
- The same Apache Amabari is behind the Hortonworks Management Console
- For Data integration, HDP offers WebHDFS, HCatalog APIs, and Talend Open Studio
- Apache HCatalog is the solution offering metadata and table management
Hortonworks Data Platform is 100% open source—I really appreciate Hortonworks’s dedication to the Apache Hadoop project and open source community
- HDP comes with 3 levels of support subscriptions, pricing starting at $12500/year for a 10 nodes cluster
One of the most interesting aspects of the Hortonworks Data Platform release is that the high-availability (HA) option for HDP is based on using VMWare-powered virtual machines for the NameNode and JobTracker. My first thought about this approach is that it was chosen to strengthen a partnership with VMWare. On the other hand, Hadoop 2.0 contains already a new highly-available version of the NameNode (Cloudera Hadoop Distribution uses this solution) and VMWare has bigger plans for a virtualization-friendly Hadoop environment with project Serengeti.
Original title and link: Hortonworks Data Platform 1.0 ( ©myNoSQL)