Here you can find all the documentation related to stratio products, ordered from newest to oldest.
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Lucene’s search technology integration with cassandra provides:
What is drools?
Drools is a Business Rules Management System (BRMS) solution. It provides a core Business Rule Engine (BRE), a web authoring and rules management application (Drools Workbench).
Drools is a Rule Engine that uses the rule based approach to implement an Expert system. A production rule is a two-part structure using First Order Logic for reasoning over knowledge representation.
The inference engine matches the rules against the facts (objects) in memory and can match the next set of rules based on the changed facts.
Benefits of drools & decision
With Stratio Decision you can launch ad-hoc queries (even remove them) by using an SQL-like language. Queries let you connect streams or operate with events in a stream in Real-Time. They only start working when you add the query to the engine and these are continuous queries. There are a lot of CEP operators that you can use in your queries:
Example: from sensor_grid #window.length(10) select name, ind, avg(data) as data group by name insert into sensor_grid_avg for current-events>
Is Stratio Streaming multi-persistence?
For sure, we have included ready-to-use actions in the engine that allows you, any time, to start or stop saving all the events in that stream to the persistence of your choice: MongoDB, Cassandra or ElasticSearch.
The engine takes care about creating keyspaces, tables, collections, indexes or whatever it needs to properly store the events (what’s more, if the stream is changed by an alter request, Stratio Streaming will also change the persistence for you).
Can I work with temporal windows?
Time is a first-class citizen in a CEP engine so yes, you can work with temporal windows. Anyway, length windows and others are also supported, and there are a lot of operators for your queries (avg, count, sum, max, min, patterns, sequences, joins…)
How can I send data to the engine?
Use the API or the Shell provided by Stratio Streaming. You can send a really BIG amount of events.
Apache Flume is a distributed, reliable, and available system for efficiently collecting, aggregating and moving large amounts of log data from many different sources to a centralized data store.
Its use is not only designed for logs, in fact you can find a myriad of sources, sinks and transformations.
In addition, a sink could be a final big data storage but also another real-time system (Apache Kafka, Spark Streaming)
Stratio ingestion is a fork of apache flume (1.6) where you can find:
Stratio Intelligence is the Data Intelligence layer of the Data-centric architecture. The main milestones of Stratio Intelligence are:
Stratio Manager is the easiest way to install, manage and monitor all the technology stack related to Spark.
Choose your cluster size, select which software to install and let Stratio Manager do all the hard work.
USE YOUR OWN SERVERS (UBUNTU, CENTOS OR RHEL) OR CLOUD DEPLOYMENT OF CHOICE (AMAZON EC2).
Stratio Sparta is a pure spark real-time aggregation engine. With absolutely no coding, you can simultaneously deploy several user-defined aggregation workflows, where you can decide which rollups and dimensions will be applied to the event stream, in real-time.
Each workflow has its own aggregation policy where you can select which input (Kafka, Flume, Twitter, etc.), output (MongoDB, Cassandra, etc.), event parser functions (decoding, enrichment, normalization), and aggregation functions (time-based, geo-range, hierarchical counting, sum, max, min, count, sumsquares, etc.) will be executed by Sparta.
Without generating a single line of code, using an easy and friendly interface, you can define your aggregation policies needs, including:
Data is worthless if you don’t communicate it correctly. Stratio Viewer was born out of the need to explain the real value of data. Our content-centred approach to data lets you focus on what to you really want to communicate: dashboards, reports, microsites... Stratio Viewer lets you use an array of widgets and a wide catalogue of data sources, based on mature market standards.
The following video is a short overview of some of the features and capabilities which Viewer offers you:
Using the native connectors you can communicate with any source in its own language (SQL, CQL, Mongo QL, Lucene syntax, Json...). Furthermore, if you don't know the source's dialect you can use our SQL data sources and use your SQL skills to get data from any source.
Apache Sqoop is a tool designed for efficiently transferring bulk data from structured datastores such as relational databases to different places. Sqoop works in batch mode and commonly it's used to import high volumes of data from big databases and store it in a data lake.
Apache Sqoop works on top of Hadoop but in Stratio we've adapted Sqoop to work also on top of Spark. At this way Sqoop on top of Spark is a perfect tool to import high volumes of data in a efficient way and send it for example to Kafka to be Ingested in your Big Data platform.
Stratio allows you give the next step and run all the jobs operations that you ran in a Hadoop cluster in a Spark cluster providing you all the Spark beneficts.
The traditional application management system, that is, the interaction of applications with relational database using RDBMS, is one of the sources that generate Big Data. Such Big Data, generated by RDBMS, is stored in Relational Database Servers in the relational database structure.
When Big Data storages and analyzers such as MapReduce, Hive, HBase, Cassandra, Pig, etc. of the Hadoop ecosystem came into picture, they required a tool to interact with the relational database servers for importing and exporting the Big Data residing in them. Here, Sqoop occupies a place in the Hadoop ecosystem to provide feasible interaction between relational database server and Hadoop’s HDFS.
Sqoop is a tool designed to transfer data between Hadoop and relational database servers. It is used to import data from relational databases such as MySQL, Oracle to Hadoop HDFS, and export from Hadoop file system to relational databases. It is provided by the Apache Software Foundation.
From a high level point of view, Stratio goSec is a centralized security to manage fine-grained access control over the Big Data services, such as Apache HDFS, Apache Cassandra, Apache Kafka, Apache Zookeeper and also web applications, such as Stratio Viewer or Stratio Intelligence
Thanks to Stratio goSec, security administrators can easily manage policies for access to files, folders, topics, databases, tables, or znodes. These policies can be set for individual users or groups and then enforced across the platform.
Stratio goSec can also manage the audit information collected in authentication or authorization events for deeper control of the environment.
Stratio goSec currently supports authorization, authentication, auditing, security administration for the following Stratio components:
And single sign-on across:
This is the high level view of Stratio goSec components:
Stratio Morphlines add some useful transformations to the defaults Kite SDK.
Stratio Morphlines consists of several modules: