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Hybrid 
Data Architecture 
Unlock the full potential of 
your business-critical applications 
Dr. Jayaraj Poroor 
http://jayaraj.poroor.com
Data architecture defines 
Software architecture 
“Show me your flowcharts and conceal your tables, and I 
shall continue to be mystified. Show me your tables, and I 
won't usually need your flowcharts; they'll be obvious.” 
Fred Brooks 
Computer Pioneer & Turing Award* Winner 
* Turing Award is Computer Science equivalent of Nobel Prize
Benefits of proper data architecture 
● Stability 
● Scalability 
● Performance 
● Security 
● Reduced code complexity 
● Extensibility
Data Architecture: Good vs Bad 
Application 
Requirements 
Wrong Data Architecture 
Application 
Requirements 
Right Data Architecture
Not all application data are equal 
Basic 
Domain 
Data 
Time-tagged 
Log Data 
Relationship 
Data 
Unstructured 
Text 
Session 
Data 
The same application may have diverse data requirements.
Force fit all data into the same 
data store? 
● Poor performance/scalability 
● Complex application code 
○ Slow/buggy 
Application’s diverse data 
requirements. 
A single data store won’t fit all 
requirements
Hybrid Data Architecture 
● Use the right kind of data store for each 
different kind of data requirement.
Data stores: sheer variety 
1. Key-value data stores, e.g., Memcached, Redis, Amazon SimpleDB, Amazon S3. 
2. Distributed key-value data stores, e.g., Riak, Amazon DynamoDB. 
3. In-process key-value data stores, e.g., Level-DB, Berkeley DB, MapDB. 
4. Unstructured/semi-structured search databases, e.g., ElasticSearch, Apache SOLR. 
5. Time series databases, e.g., TempoDB, InfluxDB, OpenTSDB. 
6. Column family databases, e.g., Apache HBase, Cassandra, Google BigTable (Cloud Datastore). 
7. Document databases, e.g. CouchBase, CouchDB, MongoDB, Terrastore, RavenDB. 
8. Graph databases, e.g., Neo4J, InfiniteGraph, InfoGrid, OrientDB, FlockDB. 
9. SQL databases, e.g., MySQL, MariaDB, PostgreSQL. 
10. In-process (embedded) SQL databases, e.g., HSQLDB, Apache Derby, Sqlite. 
11. XML databases, e.g., ExistDB, Sedna, BaseX. 
12. Logic-based data stores, e.g., Datomic, Jena.
About Me 
● 19+ years of experience in industry and 
research settings. 
○ Holds PhD in Computer Science 
● Has been architecting software systems 
for 14 years. 
● Hands-on experience with diverse 
programming languages/platforms in 
web/mobile/embedded worlds.
Hybrid Data Architecture 
consultancy services 
● Understanding your application requirements and developing a hybrid data 
architecture and design that best suites your application needs. 
○ I can advise at CTO level or directly work with tech leads. 
● Giving hands-on training sessions to the developers to help them come up 
to speed on various database technologies. 
● Helping developers integrate hybrid data access into the application code. 
● Helping your sysadmin get the various databases installed and configured 
in your servers or in a cloud platform such as the AWS.
Real project cases 
(1) Migrating from pure MySQL to hybrid MySQL/Amazon 
S3 improved an application’s performance by a factor of 
5 and reduced the main transactional database size by 
a factor of 50. 
(2) Migrating from pure MySQL-based system to a hybrid 
architecture of MySQL/ElasticSearch/Neo4J reduced 
the application code complexity significantly and 
reduced development/testing time.
Real project cases (2) 
(3) Employing a hybrid architecture of 
MySQL/Redis/InfluxDB a highly scalable and stable IoT 
back-end application was developed in 3 month’s time 
by 2 developers. 
(4) Search performance significantly improved for a web 
application by employing a hybrid architecture of 
MySQL/ElasticSearch. 
(5) Employing Mapdb at the client-side greatly enhanced 
user experience, allowing disconnected operation.
Thank You 
Realize the full potential of your business-critical 
applications through hybrid data architecture. 
jayaraj.poroor@gmail.com 
http://jayaraj.poroor.com

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Hybrid data-arch

  • 1. Hybrid Data Architecture Unlock the full potential of your business-critical applications Dr. Jayaraj Poroor http://jayaraj.poroor.com
  • 2. Data architecture defines Software architecture “Show me your flowcharts and conceal your tables, and I shall continue to be mystified. Show me your tables, and I won't usually need your flowcharts; they'll be obvious.” Fred Brooks Computer Pioneer & Turing Award* Winner * Turing Award is Computer Science equivalent of Nobel Prize
  • 3. Benefits of proper data architecture ● Stability ● Scalability ● Performance ● Security ● Reduced code complexity ● Extensibility
  • 4. Data Architecture: Good vs Bad Application Requirements Wrong Data Architecture Application Requirements Right Data Architecture
  • 5. Not all application data are equal Basic Domain Data Time-tagged Log Data Relationship Data Unstructured Text Session Data The same application may have diverse data requirements.
  • 6. Force fit all data into the same data store? ● Poor performance/scalability ● Complex application code ○ Slow/buggy Application’s diverse data requirements. A single data store won’t fit all requirements
  • 7. Hybrid Data Architecture ● Use the right kind of data store for each different kind of data requirement.
  • 8. Data stores: sheer variety 1. Key-value data stores, e.g., Memcached, Redis, Amazon SimpleDB, Amazon S3. 2. Distributed key-value data stores, e.g., Riak, Amazon DynamoDB. 3. In-process key-value data stores, e.g., Level-DB, Berkeley DB, MapDB. 4. Unstructured/semi-structured search databases, e.g., ElasticSearch, Apache SOLR. 5. Time series databases, e.g., TempoDB, InfluxDB, OpenTSDB. 6. Column family databases, e.g., Apache HBase, Cassandra, Google BigTable (Cloud Datastore). 7. Document databases, e.g. CouchBase, CouchDB, MongoDB, Terrastore, RavenDB. 8. Graph databases, e.g., Neo4J, InfiniteGraph, InfoGrid, OrientDB, FlockDB. 9. SQL databases, e.g., MySQL, MariaDB, PostgreSQL. 10. In-process (embedded) SQL databases, e.g., HSQLDB, Apache Derby, Sqlite. 11. XML databases, e.g., ExistDB, Sedna, BaseX. 12. Logic-based data stores, e.g., Datomic, Jena.
  • 9. About Me ● 19+ years of experience in industry and research settings. ○ Holds PhD in Computer Science ● Has been architecting software systems for 14 years. ● Hands-on experience with diverse programming languages/platforms in web/mobile/embedded worlds.
  • 10. Hybrid Data Architecture consultancy services ● Understanding your application requirements and developing a hybrid data architecture and design that best suites your application needs. ○ I can advise at CTO level or directly work with tech leads. ● Giving hands-on training sessions to the developers to help them come up to speed on various database technologies. ● Helping developers integrate hybrid data access into the application code. ● Helping your sysadmin get the various databases installed and configured in your servers or in a cloud platform such as the AWS.
  • 11. Real project cases (1) Migrating from pure MySQL to hybrid MySQL/Amazon S3 improved an application’s performance by a factor of 5 and reduced the main transactional database size by a factor of 50. (2) Migrating from pure MySQL-based system to a hybrid architecture of MySQL/ElasticSearch/Neo4J reduced the application code complexity significantly and reduced development/testing time.
  • 12. Real project cases (2) (3) Employing a hybrid architecture of MySQL/Redis/InfluxDB a highly scalable and stable IoT back-end application was developed in 3 month’s time by 2 developers. (4) Search performance significantly improved for a web application by employing a hybrid architecture of MySQL/ElasticSearch. (5) Employing Mapdb at the client-side greatly enhanced user experience, allowing disconnected operation.
  • 13. Thank You Realize the full potential of your business-critical applications through hybrid data architecture. jayaraj.poroor@gmail.com http://jayaraj.poroor.com