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Real-time replication vs ETL - How analytics requires new
technologies designed for it, not '70s technology
Topics
In today’s webinar, we will discuss:
• What is ETL?
• What is CDC?
• What is replication?
• Differences
Extract, Transform, and Load (ETL)
SELECT *
FROM XXX
Transform
(Datatypes,
structure,
Embedded types)
INSERT INTO
YYY
ETL Latency
Every
Hour, or
Day, or
Week
Large Blocks
ETL Incremental
Track primary key, load PKey from Last
Track existing timestamp, extract from last TS
Modify structure to add timestamp
or change tag
ETL Parameters
Advantages
• Loads large blocks of data efficiently
• Allows for complex and detailed transformation
• Allows for full data extraction
• Can be easy to implement
• Efficient data loading for some target environments
Disadvantages
• Can be time consuming
• Places extreme load on source database
• Transformation can take excessive time
• Bulk load can create data ingestion performance
problems on the target database
• Incremental loading difficult or complex
– Either timestamp based
– Data/structure changes
Change Data Capture (CDC)
INSERT,
UPDATE,
DELETE
Trigger or
Background Process
Modified Rows
Copy to
Target
CDC Latency
LoadCDC
Generation
Row
Extraction
CDC Parameters
Advantages
• Easy method of identify or extracting data
• Requires no schema modifications to the source
database
• Medium latency
• Medium data loading cadence
Disadvantages
• Requires database level support
– Either custom CDC or Triggers
• Requires additional database and table space
• Implies overhead on database (both for generation
and extraction)
• Extraction latency can increase as data volumes
increase
• Requires source access to DB
• No or few transformations
Replication
DBMS
Logs
Master Replicator:
Extractor
Slave Replicator:
Applier
Replication Latency
Transaction
Batch
Replication Parameters
Advantages
• Low latency replication
• No source database access
• No source database load
• No source database changes
Disadvantages
• Limited transformation and combination of data
• Per-transaction loads slower
– Mitigated by batching or parallel apply
Comparison
Feature ETL CDC Replication
Data Rate Low, periodic Periodic High, real-time
Transformations All data and modifications
possible before load
Very low complexity only Low complexity only
Combination Complex combinations
possible
Very limited Very limited
Source DB Load Impact High to Very High Medium Low
Incremental Support Difficult, or requires DDL
changes
Fully supported Fully supported
Example of modern Heterogeneous Deployments
Replicator
Warehouse
Per User
Per Database
Audit
Conclusions
• ETL
– Efficient and simple system
– Slow, and not usable for modern deployments
– Incremental Complex
• CDC
– Capable with database load
– Lower latency
– DB dependent
• Replication
– Very low latency/High performance
– Limited transformations and combinations
Next Steps
• If you are interested in knowing more about Tungsten Replicator and would like to try it out for
yourself, please contact our sales team who will be able to take you through the details and
setup a POC – sales@continuent.com
• Read the documentation at http://docs.continuent.com/tungsten-replicator-5.2/index.html
• Subscribe to our Tungsten University YouTube channel! http://tinyurl.com/TungstenUni
For more information, contact us:
Eric Stone
COO
eric.stone@continuent.com
MC Brown
VP Products
mc.brown@continuent.com
Chris Parker
Director, Professional Services EMEA & APAC
chris.parker@continuent.com
Eero Teerikorpi
Founder, CEO
eero.teerikorpi@continuent.com
+1 (408) 431-3305

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Webinar Slides: Real-Time Replication vs. ETL - How Analytics Requires New Technologies Designed For It, Not '70s Technology

  • 1. Real-time replication vs ETL - How analytics requires new technologies designed for it, not '70s technology
  • 2. Topics In today’s webinar, we will discuss: • What is ETL? • What is CDC? • What is replication? • Differences
  • 3. Extract, Transform, and Load (ETL) SELECT * FROM XXX Transform (Datatypes, structure, Embedded types) INSERT INTO YYY
  • 4. ETL Latency Every Hour, or Day, or Week Large Blocks
  • 5. ETL Incremental Track primary key, load PKey from Last Track existing timestamp, extract from last TS Modify structure to add timestamp or change tag
  • 6. ETL Parameters Advantages • Loads large blocks of data efficiently • Allows for complex and detailed transformation • Allows for full data extraction • Can be easy to implement • Efficient data loading for some target environments Disadvantages • Can be time consuming • Places extreme load on source database • Transformation can take excessive time • Bulk load can create data ingestion performance problems on the target database • Incremental loading difficult or complex – Either timestamp based – Data/structure changes
  • 7. Change Data Capture (CDC) INSERT, UPDATE, DELETE Trigger or Background Process Modified Rows Copy to Target
  • 9. CDC Parameters Advantages • Easy method of identify or extracting data • Requires no schema modifications to the source database • Medium latency • Medium data loading cadence Disadvantages • Requires database level support – Either custom CDC or Triggers • Requires additional database and table space • Implies overhead on database (both for generation and extraction) • Extraction latency can increase as data volumes increase • Requires source access to DB • No or few transformations
  • 12. Replication Parameters Advantages • Low latency replication • No source database access • No source database load • No source database changes Disadvantages • Limited transformation and combination of data • Per-transaction loads slower – Mitigated by batching or parallel apply
  • 13. Comparison Feature ETL CDC Replication Data Rate Low, periodic Periodic High, real-time Transformations All data and modifications possible before load Very low complexity only Low complexity only Combination Complex combinations possible Very limited Very limited Source DB Load Impact High to Very High Medium Low Incremental Support Difficult, or requires DDL changes Fully supported Fully supported
  • 14. Example of modern Heterogeneous Deployments Replicator Warehouse Per User Per Database Audit
  • 15. Conclusions • ETL – Efficient and simple system – Slow, and not usable for modern deployments – Incremental Complex • CDC – Capable with database load – Lower latency – DB dependent • Replication – Very low latency/High performance – Limited transformations and combinations
  • 16. Next Steps • If you are interested in knowing more about Tungsten Replicator and would like to try it out for yourself, please contact our sales team who will be able to take you through the details and setup a POC – sales@continuent.com • Read the documentation at http://docs.continuent.com/tungsten-replicator-5.2/index.html • Subscribe to our Tungsten University YouTube channel! http://tinyurl.com/TungstenUni
  • 17. For more information, contact us: Eric Stone COO eric.stone@continuent.com MC Brown VP Products mc.brown@continuent.com Chris Parker Director, Professional Services EMEA & APAC chris.parker@continuent.com Eero Teerikorpi Founder, CEO eero.teerikorpi@continuent.com +1 (408) 431-3305