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14 Top Data Pipeline Key Terms Explained

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 Here are some key terms commonly used in data pipelines 1. Data Sources Definition: Points where data originates (e.g., databases, APIs, files, IoT devices). Examples: Relational databases (PostgreSQL, MySQL), APIs, cloud storage (S3), streaming data (Kafka), and on-premise systems. 2. Data Ingestion Definition: The process of importing or collecting raw data from various sources into a system for processing or storage. Methods: Batch ingestion, real-time/streaming ingestion. 3. Data Transformation Definition: Modifying, cleaning, or enriching data to make it usable for analysis or storage. Examples: Data cleaning (removing duplicates, fixing missing values). Data enrichment (joining with other data sources). ETL (Extract, Transform, Load). ELT (Extract, Load, Transform). 4. Data Storage Definition: Locations where data is stored after ingestion and transformation. Types: Data Lakes: Store raw, unstructured, or semi-structured data (e.g., S3, Azure Data Lake). Data Warehous...
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HBASE: Top Features in Storing Big data

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In this post explained top features added in HBase to handle the data. The Java implementation of Google's Big Table you can call it as HBASE.  In HBase, the data store as two parts.
hadoop hbase

Row Key : 00001 
Column : (Column Qualifier:Version:Value)

Features of HBASE

  • HBase data stores consist of one or more tables, which are indexed by row keys.
  • Data is stored in rows with columns, and rows can have multiple versions.
  • By default, data versioning for rows is implemented with time stamps.
  • Columns are grouped into column families, which must be defined upfront during table creation. Column families are stored together on disk, which is why HBase is referred to as a column-oriented datastore
New features of HBASE check now

In addition...

HBase is a distributed data store, which leverages a network-attached cluster of low-cost commodity servers to store and persist data.HBase architecture is a little trick to know.

Region Servers...

RegionServers are the software processes (often called daemons) you activate to store and retrieve data in HBase.

The big difference...

  • HABSE handles growing data or big data. HBase automatically scales as you add data to the system. A huge benefit compared to most database management systems, which require manual intervention to scale the overall system beyond a single server. 
  • With HBase, as long as you have in the rack another spare server that's configured, scaling is automatic.

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