What are big data tools used currently in market?

Big data is a broad term for data sets so large or complex that traditional data processing applications are inadequate.

Traditional SQL databases used for storing and retrieving data. It all depends on the use cases. In contrast, nonSQL databases are in-memory caches, full-text search engines, real-time streaming, graph databases, etc.

Cassandra: An open source distributed database management system originally developed at Facebook and designed to handle large amounts of data across many commodity servers, providing high availability with no single point of failure.

Redis: An open source (BSD licensed), in-memory data structure store, used as database, cache and message broker.

CouchBase: An open-source, distributed NoSQL document-oriented database that is optimized for interactive applications.

CouchDB: An open-source document-oriented NoSQL database that uses JSON to store data.

MongoDB: A popular, a cross-platform document-oriented database.

Elasticsearch: A distributed RESTful search engine built for the cloud.

Hazelcast: An open source in-memory data grid based on Java.

EHCache : A widely used open source Java distributed cache for general purpose caching, Java EE and light-weight containers.

Hadoop : An open-source software framework written in Java for distributed storage and distributed processing of very large data sets on computer clusters built from commodity hardware.

HBase : An open source, non-relational, distributed database modeled after Google's BigTable, written in Java and runs on top of HDFS.

Spark Spark : An open source cluster computing framework.

Memcached : A general-purpose distributed memory caching system.

Apache Hive : It provides an SQL-like layer on top of Hadoop.

Apache Kafka : A high-throughput, distributed, publish-subscribe messaging system originally developed at LinkedIn.

Akka: A toolkit and runtime for building highly concurrent, distributed, and resilient message-driven applications on the JVM.

Neo4j: An open-source graph database implemented in Java.

Solr: An open source enterprise search platform, written in Java, from the Apache Lucene project.

Apache Storm: An open source distributed realtime computation system.

Oracle Coherence: An in-memory data grid solution that enables organizations to predictably scale mission-critical applications by providing fast access to frequently used data.

Titan: A scalable graph database optimized for storing and querying graphs containing hundreds of billions of vertices and edges distributed across a multi-machine cluster.

Amazon DynamoDB: A fast and flexible fully managed NoSQL database service for all applications that need consistent, single-digit millisecond latency at any scale.

Amazon Kinesis: A platform for streaming data real-time on AWS.

Datomic: A fully transactional, cloud-ready, distributed database written in Clojure.

What is big file tablespace in oracle?

A big file tablespace is a single tablespace can have  very large  - up to 4G blocks in a data file. As compare to traditional tablespaces which can contain multiple data files, but the files cannot be as large.

Some benefits of its are as under:

• A Bigfile tablespace with 8K/16K/32K blocks can contain a 32/64/128 TB data file. 
• The maximum number of datafiles in an Oracle Database is limited to Max. 64K files. 
• A Bigfile tablespace can significantly improve the storage capacity of the Database.
• Bigfile tablespaces reduce the number of data files for a database, with this DB_FILES initialization parameter and MAXDATAFILES parameter of the CREATE DATABASE and CREATE CONTROLFILE statements can be adjusted by DBA to reduce the amount of SGA space required for data files and size of the control file.
• Bigfile tablespaces simplify database management by providing data file transparency instead of using multiple data files.
• It supports only for locally managed tablespaces with automatic segment space management, and it’s not used for locally managed undo tablespaces, temporary tablespaces and SYSTEM tablespace.
• It is advised to use big file tablespaces in a database where Automatic Storage Management (ASM) configured or other logical volume managers that support striping or RAID, and dynamically extensible logical volumes.
• Avoid creating big file tablespaces on a database that is not supporting striping because of negative implications for parallel query execution and RMAN backup parallelization.

If the default tablespace type is specified to BIGFILE at a time of database creation, you need not specify the keyword BIGFILE in the CREATE TABLESPACE statement. A big file tablespace is created by default.

CREATE BIGFILE TABLESPACE tbs_bigtable_ex1
DATAFILE '/u02/oracle/data/tbsbig01.dbf' SIZE 80G;

If the default tablespace type is specified to BIGFILE at a time of database creation, but you want to create a traditional - small file tablespace, then uses a CREATE SMALLFILE TABLESPACE statement to override the default tablespace type which creating database.

CREATE SMALLFILE TABLESPACE tbs_smalltable_ex1
DATAFILE '/u02/oracle/data/tbssmall01.dbf' SIZE 80G;