The difference between Magento 1 and Magento 2 database is huge. Here are a significant number of changes in the database structure that are worth highlighting.
Partitioning on Oracle 12c - What changed on the most important Oracle featureLuis Marques
It was introduced in Oracle 8.0 in 1997 and since then Oracle Partitioning is mandatory for a big number Oracle Database architectures and implementations to ensure that high availabity or multi-terabyte systems keep the performance requirements.
This talk will demonstrate the improvements made in Oracle Partition on 12c from new interval reference partitions to partial partitioned and global async global indexes and how the today's critical Oracle databases that still run on 11g can revamp on this set of features.
Topic Objective: This topic is about Oracle Partition, the most used and most important paid option of Oracle Database. Learning how 12c improved it is vital for any Oracle DBA. Using this new set of new features can reduce your downtime, save DBA time and reduce the number of DBA "workarounds" to deal with specific situations when current 11g set of partition features is limited.
These slides use concepts from my (Jeff Funk) course entitled Biz Models for Hi-Tech Products to analyze the business model for Uber’s taxi service. Uber’s service enables anyone to provide taxi services and it provides dynamic pricing for better matching of supply and demand. Its value proposition for potential drivers is the opportunity to work as driver on their own hours. Its value proposition for user to lower taxi fares during most times of the day and a higher supply of taxis (and higher prices) during peak demand. The customers are tech-savvy and smart phone users who value their time. Uber receives payments directly from customers and keeps a percentage of these payments as its income. Uber’s patents for a demand-price algorithm represent a barrier of entry and thus a method of strategic control.
Magento 2 Database Tables, Schema, Main tables for main features of Magento 2...gideonvbabu
We prepared this presentation to teach interns and Magento newbies about Magento database structure and important tables.
We have added most import tables used for e-Commerce function like categories, products, customer, admin, shopping cart, sales order, wishlist, cache and index, tmp, idx tables.
Please feel free to add your feedback in the comment section and like it if you find it useful.
If you have any queries, please connect with at www.linkedin.co/in/gideon-babu/
Thank you,
-Gideon
A brief introduction to the Declarative Schema introduced into Magento 2.3.
This presentation covers:
- What developers were required to do previously
- The benefits of using Declarative Schema
- How to create tables
- How to rename tables
- How to drop tables
- Table attributes
- Adding columns
- Column attributes
- Indexes
- Unique values within columns
- Primary keys
- Foreign keys
- Data patches and how to create them
- Schema patches and how to create them
Partitioning on Oracle 12c - What changed on the most important Oracle featureLuis Marques
It was introduced in Oracle 8.0 in 1997 and since then Oracle Partitioning is mandatory for a big number Oracle Database architectures and implementations to ensure that high availabity or multi-terabyte systems keep the performance requirements.
This talk will demonstrate the improvements made in Oracle Partition on 12c from new interval reference partitions to partial partitioned and global async global indexes and how the today's critical Oracle databases that still run on 11g can revamp on this set of features.
Topic Objective: This topic is about Oracle Partition, the most used and most important paid option of Oracle Database. Learning how 12c improved it is vital for any Oracle DBA. Using this new set of new features can reduce your downtime, save DBA time and reduce the number of DBA "workarounds" to deal with specific situations when current 11g set of partition features is limited.
These slides use concepts from my (Jeff Funk) course entitled Biz Models for Hi-Tech Products to analyze the business model for Uber’s taxi service. Uber’s service enables anyone to provide taxi services and it provides dynamic pricing for better matching of supply and demand. Its value proposition for potential drivers is the opportunity to work as driver on their own hours. Its value proposition for user to lower taxi fares during most times of the day and a higher supply of taxis (and higher prices) during peak demand. The customers are tech-savvy and smart phone users who value their time. Uber receives payments directly from customers and keeps a percentage of these payments as its income. Uber’s patents for a demand-price algorithm represent a barrier of entry and thus a method of strategic control.
Magento 2 Database Tables, Schema, Main tables for main features of Magento 2...gideonvbabu
We prepared this presentation to teach interns and Magento newbies about Magento database structure and important tables.
We have added most import tables used for e-Commerce function like categories, products, customer, admin, shopping cart, sales order, wishlist, cache and index, tmp, idx tables.
Please feel free to add your feedback in the comment section and like it if you find it useful.
If you have any queries, please connect with at www.linkedin.co/in/gideon-babu/
Thank you,
-Gideon
A brief introduction to the Declarative Schema introduced into Magento 2.3.
This presentation covers:
- What developers were required to do previously
- The benefits of using Declarative Schema
- How to create tables
- How to rename tables
- How to drop tables
- Table attributes
- Adding columns
- Column attributes
- Indexes
- Unique values within columns
- Primary keys
- Foreign keys
- Data patches and how to create them
- Schema patches and how to create them
With help of this small Proof of Concept, I have tried to demonstrate the usage of Neo4J (Graph DB) as a metastore for a Data Lake or a DW. Graph DBs can store highly relational data and help us in doing data discovery and impact analysis, which bit more complex to bee done in an RDBMS.
Restoring Abandoned Destroyed Phone, Found a lot of broken phones and more!https://linktr.ee/hmaadi https://linktr.ee/hmaad
Restoring Abandoned Destroyed Phone, Found a lot of broken phones and more!https://linktr.ee/hmaadi https://linktr.ee/hmaadihttps://uii.io/ref/hmaadihttps://uii.io/ref/hmaadii
Adding Custom Fields to your WooCommerce products are a great way to show custom data on your product pages. This presentation will show you how to add Custom Fields to your Simple & Grouped products as well as adding them to Variable Products.
SenchaCon 2016: Upgrading an Ext JS 4.x Application to Ext JS 6.x - Mark Linc...Sencha
In this session we'll demonstrate the optimal way to upgrade an Ext JS 4.x application to Ext JS 6.x. Detailed examples, recommended best practices, and a completely upgraded Ext JS application will be demonstrated showing the techniques used to perform the upgrade.
Features:
Immutable and Transparent: Append-only journal and Easy access to change history.
Cryptographically Verifiable: Allows to verify the the changes, through the History called as Digest.
Serverless: Easy to Scale, Easy setup and Easy Monitoring and metrics.
Easy to Use: Uses, PartiQL as SQL for querying. Which is a Document-oriented data model with the Transactional Consistency and ACID Semantics.
Streaming Capability:
Adding Value to HBase with IBM InfoSphere BigInsights and BigSQLPiotr Pruski
This is the extended deck I used for my presentation at the Information On Demand 2013 conference for Session Number 1687 - Adding Value to HBase with IBM InfoSphere BigInsights and BigSQL.
This presentation covers accessing HBase using Big SQL. It starts by going over general HBase concepts, than delves into how Big SQL adds an SQL layer on top of HBase (via HBase storage handler), secondary index support, queries, etc.
http://www.it-exams.fr/70-467.htm Le service après-vente est notre préoccupation principale. Nous cherchons à satisfaire tous les clients. En respectant le principe « le client d’abord » , nous faisons en sorte que tous les acheteurs réussissent à l’examen( Microsoft 70-467 (TS:Designing Business Intelligence Solutions with Microsoft SQL Server 2012) ). Garantir la confidentialité des données personnelles des clients fait fondamentalement partie de notre politique. Nous veillons à protéger strictement les informations personnelles des clients et à ne pas révéler, modifier ou divulguer les dossiers d’inscription et les informations non publiées sans autorisation des clients.
Experience our free, in-depth three-part Tendenci Platform Corporate Membership Management workshop series! In Session 1 on May 14th, 2024, we began with an Introduction and Setup, mastering the configuration of your Corporate Membership Module settings to establish membership types, applications, and more. Then, on May 16th, 2024, in Session 2, we focused on binding individual members to a Corporate Membership and Corporate Reps, teaching you how to add individual members and assign Corporate Representatives to manage dues, renewals, and associated members. Finally, on May 28th, 2024, in Session 3, we covered questions and concerns, addressing any queries or issues you may have.
For more Tendenci AMS events, check out www.tendenci.com/events
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
More Related Content
Similar to Magento 1 vs Magento 2 Database Structure
With help of this small Proof of Concept, I have tried to demonstrate the usage of Neo4J (Graph DB) as a metastore for a Data Lake or a DW. Graph DBs can store highly relational data and help us in doing data discovery and impact analysis, which bit more complex to bee done in an RDBMS.
Restoring Abandoned Destroyed Phone, Found a lot of broken phones and more!https://linktr.ee/hmaadi https://linktr.ee/hmaad
Restoring Abandoned Destroyed Phone, Found a lot of broken phones and more!https://linktr.ee/hmaadi https://linktr.ee/hmaadihttps://uii.io/ref/hmaadihttps://uii.io/ref/hmaadii
Adding Custom Fields to your WooCommerce products are a great way to show custom data on your product pages. This presentation will show you how to add Custom Fields to your Simple & Grouped products as well as adding them to Variable Products.
SenchaCon 2016: Upgrading an Ext JS 4.x Application to Ext JS 6.x - Mark Linc...Sencha
In this session we'll demonstrate the optimal way to upgrade an Ext JS 4.x application to Ext JS 6.x. Detailed examples, recommended best practices, and a completely upgraded Ext JS application will be demonstrated showing the techniques used to perform the upgrade.
Features:
Immutable and Transparent: Append-only journal and Easy access to change history.
Cryptographically Verifiable: Allows to verify the the changes, through the History called as Digest.
Serverless: Easy to Scale, Easy setup and Easy Monitoring and metrics.
Easy to Use: Uses, PartiQL as SQL for querying. Which is a Document-oriented data model with the Transactional Consistency and ACID Semantics.
Streaming Capability:
Adding Value to HBase with IBM InfoSphere BigInsights and BigSQLPiotr Pruski
This is the extended deck I used for my presentation at the Information On Demand 2013 conference for Session Number 1687 - Adding Value to HBase with IBM InfoSphere BigInsights and BigSQL.
This presentation covers accessing HBase using Big SQL. It starts by going over general HBase concepts, than delves into how Big SQL adds an SQL layer on top of HBase (via HBase storage handler), secondary index support, queries, etc.
http://www.it-exams.fr/70-467.htm Le service après-vente est notre préoccupation principale. Nous cherchons à satisfaire tous les clients. En respectant le principe « le client d’abord » , nous faisons en sorte que tous les acheteurs réussissent à l’examen( Microsoft 70-467 (TS:Designing Business Intelligence Solutions with Microsoft SQL Server 2012) ). Garantir la confidentialité des données personnelles des clients fait fondamentalement partie de notre politique. Nous veillons à protéger strictement les informations personnelles des clients et à ne pas révéler, modifier ou divulguer les dossiers d’inscription et les informations non publiées sans autorisation des clients.
Similar to Magento 1 vs Magento 2 Database Structure (20)
Experience our free, in-depth three-part Tendenci Platform Corporate Membership Management workshop series! In Session 1 on May 14th, 2024, we began with an Introduction and Setup, mastering the configuration of your Corporate Membership Module settings to establish membership types, applications, and more. Then, on May 16th, 2024, in Session 2, we focused on binding individual members to a Corporate Membership and Corporate Reps, teaching you how to add individual members and assign Corporate Representatives to manage dues, renewals, and associated members. Finally, on May 28th, 2024, in Session 3, we covered questions and concerns, addressing any queries or issues you may have.
For more Tendenci AMS events, check out www.tendenci.com/events
Developing Distributed High-performance Computing Capabilities of an Open Sci...Globus
COVID-19 had an unprecedented impact on scientific collaboration. The pandemic and its broad response from the scientific community has forged new relationships among public health practitioners, mathematical modelers, and scientific computing specialists, while revealing critical gaps in exploiting advanced computing systems to support urgent decision making. Informed by our team’s work in applying high-performance computing in support of public health decision makers during the COVID-19 pandemic, we present how Globus technologies are enabling the development of an open science platform for robust epidemic analysis, with the goal of collaborative, secure, distributed, on-demand, and fast time-to-solution analyses to support public health.
Into the Box Keynote Day 2: Unveiling amazing updates and announcements for modern CFML developers! Get ready for exciting releases and updates on Ortus tools and products. Stay tuned for cutting-edge innovations designed to boost your productivity.
Providing Globus Services to Users of JASMIN for Environmental Data AnalysisGlobus
JASMIN is the UK’s high-performance data analysis platform for environmental science, operated by STFC on behalf of the UK Natural Environment Research Council (NERC). In addition to its role in hosting the CEDA Archive (NERC’s long-term repository for climate, atmospheric science & Earth observation data in the UK), JASMIN provides a collaborative platform to a community of around 2,000 scientists in the UK and beyond, providing nearly 400 environmental science projects with working space, compute resources and tools to facilitate their work. High-performance data transfer into and out of JASMIN has always been a key feature, with many scientists bringing model outputs from supercomputers elsewhere in the UK, to analyse against observational or other model data in the CEDA Archive. A growing number of JASMIN users are now realising the benefits of using the Globus service to provide reliable and efficient data movement and other tasks in this and other contexts. Further use cases involve long-distance (intercontinental) transfers to and from JASMIN, and collecting results from a mobile atmospheric radar system, pushing data to JASMIN via a lightweight Globus deployment. We provide details of how Globus fits into our current infrastructure, our experience of the recent migration to GCSv5.4, and of our interest in developing use of the wider ecosystem of Globus services for the benefit of our user community.
Enhancing Research Orchestration Capabilities at ORNL.pdfGlobus
Cross-facility research orchestration comes with ever-changing constraints regarding the availability and suitability of various compute and data resources. In short, a flexible data and processing fabric is needed to enable the dynamic redirection of data and compute tasks throughout the lifecycle of an experiment. In this talk, we illustrate how we easily leveraged Globus services to instrument the ACE research testbed at the Oak Ridge Leadership Computing Facility with flexible data and task orchestration capabilities.
Enhancing Project Management Efficiency_ Leveraging AI Tools like ChatGPT.pdfJay Das
With the advent of artificial intelligence or AI tools, project management processes are undergoing a transformative shift. By using tools like ChatGPT, and Bard organizations can empower their leaders and managers to plan, execute, and monitor projects more effectively.
Unleash Unlimited Potential with One-Time Purchase
BoxLang is more than just a language; it's a community. By choosing a Visionary License, you're not just investing in your success, you're actively contributing to the ongoing development and support of BoxLang.
Field Employee Tracking System| MiTrack App| Best Employee Tracking Solution|...informapgpstrackings
Keep tabs on your field staff effortlessly with Informap Technology Centre LLC. Real-time tracking, task assignment, and smart features for efficient management. Request a live demo today!
For more details, visit us : https://informapuae.com/field-staff-tracking/
OpenFOAM solver for Helmholtz equation, helmholtzFoam / helmholtzBubbleFoamtakuyayamamoto1800
In this slide, we show the simulation example and the way to compile this solver.
In this solver, the Helmholtz equation can be solved by helmholtzFoam. Also, the Helmholtz equation with uniformly dispersed bubbles can be simulated by helmholtzBubbleFoam.
Large Language Models and the End of ProgrammingMatt Welsh
Talk by Matt Welsh at Craft Conference 2024 on the impact that Large Language Models will have on the future of software development. In this talk, I discuss the ways in which LLMs will impact the software industry, from replacing human software developers with AI, to replacing conventional software with models that perform reasoning, computation, and problem-solving.
Enterprise Resource Planning System includes various modules that reduce any business's workload. Additionally, it organizes the workflows, which drives towards enhancing productivity. Here are a detailed explanation of the ERP modules. Going through the points will help you understand how the software is changing the work dynamics.
To know more details here: https://blogs.nyggs.com/nyggs/enterprise-resource-planning-erp-system-modules/
Cyaniclab : Software Development Agency Portfolio.pdfCyanic lab
CyanicLab, an offshore custom software development company based in Sweden,India, Finland, is your go-to partner for startup development and innovative web design solutions. Our expert team specializes in crafting cutting-edge software tailored to meet the unique needs of startups and established enterprises alike. From conceptualization to execution, we offer comprehensive services including web and mobile app development, UI/UX design, and ongoing software maintenance. Ready to elevate your business? Contact CyanicLab today and let us propel your vision to success with our top-notch IT solutions.
Innovating Inference - Remote Triggering of Large Language Models on HPC Clus...Globus
Large Language Models (LLMs) are currently the center of attention in the tech world, particularly for their potential to advance research. In this presentation, we'll explore a straightforward and effective method for quickly initiating inference runs on supercomputers using the vLLM tool with Globus Compute, specifically on the Polaris system at ALCF. We'll begin by briefly discussing the popularity and applications of LLMs in various fields. Following this, we will introduce the vLLM tool, and explain how it integrates with Globus Compute to efficiently manage LLM operations on Polaris. Attendees will learn the practical aspects of setting up and remotely triggering LLMs from local machines, focusing on ease of use and efficiency. This talk is ideal for researchers and practitioners looking to leverage the power of LLMs in their work, offering a clear guide to harnessing supercomputing resources for quick and effective LLM inference.
May Marketo Masterclass, London MUG May 22 2024.pdfAdele Miller
Can't make Adobe Summit in Vegas? No sweat because the EMEA Marketo Engage Champions are coming to London to share their Summit sessions, insights and more!
This is a MUG with a twist you don't want to miss.
Software Engineering, Software Consulting, Tech Lead.
Spring Boot, Spring Cloud, Spring Core, Spring JDBC, Spring Security,
Spring Transaction, Spring MVC,
Log4j, REST/SOAP WEB-SERVICES.
Accelerate Enterprise Software Engineering with PlatformlessWSO2
Key takeaways:
Challenges of building platforms and the benefits of platformless.
Key principles of platformless, including API-first, cloud-native middleware, platform engineering, and developer experience.
How Choreo enables the platformless experience.
How key concepts like application architecture, domain-driven design, zero trust, and cell-based architecture are inherently a part of Choreo.
Demo of an end-to-end app built and deployed on Choreo.
3. 1. The ‘core_website’ table was replaced with ‘store_website’ (The structure was
changed)
2. The ‘core_store’ table was replaced with ‘store’ (The structure was not changed)
3. The ‘core_store_group’ table was replaced with ‘store_group’ (The structure was
not changed)
1 - Websites, Stores, Store Views
4. 1. A new field ‘is_required_in_admin_store’ was added to the ‘catalog_eav_attribute’
table
2. Two new fields ‘attribute_group_code’ & ‘tab_group_code’ were added to the
‘eav_attribute_group’ table
3. The product attribute ‘msrp_enabled’ was replaced with ‘msrp’. Magento 2 deleted
2 core attributes ‘group_price’, ‘msrp_enabled’ and the ‘group_price’ data was
converted to ‘tier_price’
4. The category attribute ‘thumbnail’ was deleted
2 - Core Product Attributes, Custom Product
Attributes
5. 1. Structure of tables’ changes:
-- The ‘entity_type_id’ field was deleted
-- Some FOREIGN KEYs were changed
2. The ‘core_url_rewrite’ table was changed to ‘url_rewrite’ and structure was
changed.
3 - Categories
6. 1. Have more than 44 related tables
2. The structure of tables was changed:
-- The enity_type_id field was deleted
-- Some FOREING KEYs were changed
3. Product Images: A new field ‘enity_id’ was added to the
‘catalog_product_entity_media_gallery_value’ table
4. The catalog_product_index_tier_price table changes:
-- The value_id, all_groups, qty, value fields were deleted
-- The min_price field was added
5. Stock:
+ The ‘website_id’ field was added to the ‘cataloginventory_stock’,
‘cataloginventory_stock_item’ tables
+ The ‘core_url_rewrite’ table was changed to ‘url_rewrite’ (structure was changed)
4 - Products
7. 1. The ‘customer_entity’, ‘customer_address_entity ‘tables removed the
‘entity_type_id’, ‘attribute_set_id’ fields
2. The ‘customer_address_entity_datetime’, ‘customer_address_entity_decimal’,
‘customer_address_entity_int’, ‘customer_address_entity_text’,
‘customer_address_entity_varchar’, ‘customer_entity_datetime’,
‘customer_entity_decimal’, ‘customer_entity_int’, ‘customer_entity_text’,
‘customer_entity_varchar’ tables removed the ‘entity_type_id’ field
3. The ‘customer_eav_attribute’ table:
-- The ‘is_used_for_customer_segment’ field was deleted
-- Data model value was changed. For instance, the customer/attribute_data_postcode
was replaced with MagentoCustomerModelAttributeDataPostcode
5 - Customers
8. 4. EAV of customer data structure was changed, some attributes were moved to the
main table:
-- Some new fields ‘created_in’, ‘firstname’, ‘middlename’, ‘lastname’, ‘password_hash’,
‘rp_token’, ‘rp_token_created_at’, ‘prefix’, ‘suffix’, ‘dob’, ‘default_billing’,
‘default_shipping’, ‘taxvat’, ‘confirmation’, ‘gender’ were added to the
‘customer_entity’ table
5. EAV of customer_address_entity data structure was changed, some attributes were
moved from the children tables to the main table `customer_address_entity`:
-- Country_id, firstname, lastname, middlename, street, telephone, city, fax, company,
country_id, postcode, prefix, region, region_id, suffix, vat_id, vat_is_valid,
vat_request_date, vat_request_id, vat_request_success
5 - Customers (cont’)
9. 6. Magento CE 2.x changed the method of hashing passwords from md5() to sha256().
Magento 2 still supports the option md5() providing that the string ‘:0’ must be
appended to the end of ‘password_hash’
Magento 2 also supports CLI command to upgrade all password_hash using md5() to
sha256(): php -f bin/magento customer:hash:upgrade
5 - Customers (cont’)
10. 6 - (Sale) Orders, Quote, Invoices, Payments,
Shipments, Bestseller info, Rules & Coupons
1. Sales Orders tables changes:
-- The ‘sales_flat_order table’ was replaced with ‘sales_order’ (the structure was
changed)
-- The ‘sales_flat_order_address’ was replaced with ‘sales_order_address’ (the
structure was changed)
-- The ‘sales_flat_order_grid’ was replaced with ‘sales_order_grid’
-- The ‘sales_flat_order_item’ was replaced with ‘sales_order_item’ (the structure was
changed)
-- The ‘sales_flat_order_status_history’ was replaced with ‘sales_order_status_history’
-- The ‘sales_order_status_state’ (the structure was changed)
-- The ‘sales_order_tax_item’ (the structure was changed)
11. 6 - (Sale) Orders, Quote, Invoices, Payments,
Shipments, Bestseller info, Rules & Coupons
2. Max length changes in the `sales_order` table:
+ ‘store_name’, ‘shipping_method’, ‘x_forwarded_for’ have new max length 32 chars.
+ ‘applied_rule_ids has new max length chars 128
+ ‘weight’ has new max length 12
3. The `sales_order_item` table changes:
+ Magento 2 changed the method to save value of the `weee_tax_applied` field to
database: serialize() -> json_encode()
+ ‘weight’, ‘row_weight’ have new max length value 12 chars
12. 6 - (Sale) Orders, Quote, Invoices, Payments,
Shipments, Bestseller info, Rules & Coupons
4. Sales Quote:
-- The ‘sales_flat_quote’ was replaced with ‘quote’ (the structure was changed)
-- ‘sales_flat_quote_address’ was replaced with ‘quote_address’ (the structure was
changed)
-- ‘sales_flat_quote_address_item’ was replaced with ‘quote_address_item’ (the
structure was changed)
-- ‘sales_flat_quote_item’ was replaced with ‘quote_item’ (the structure was changed)
-- ‘sales_flat_quote_item_option’ was replaced with ‘quote_item_option’
-- ‘sales_flat_quote_payment’ was replaced with ‘quote_payment’ (the structure was
changed)
-- ‘sales_flat_quote_shipping_rate’ was replaced with ‘quote_shipping_rate’
-- In the `quote_address ` table:
+ ‘region’, ‘shipping_method’, ‘city’ have new max length 40 chars
+ ‘firstname’, ‘lastname’, ‘postcode’, ‘telephone’, ‘fax’ have new max length 20 chars
+ ‘country_id’ has new max length 30 chars
+ ‘weight’ has new max length 12 chars
+ ‘address_type’ has new max length 10 chars
13. 6 - (Sale) Orders, Quote, Invoices, Payments,
Shipments, Bestseller info, Rules & Coupons
5. Sales Payments:
-- ‘sales_flat_order_payment’ was replaced with ‘sales_order_payment’ (the structure
was changed)
-- The `sales_order_payment` table has some fields ‘po_number’, ‘cc_number_enc’
with max length 32 chars
6. Sales Invoices:
-- ‘sales_flat_invoice’ was replaced with ‘sales_invoice’ (the structure was changed)
-- ‘sales_flat_invoice_comment’ was replaced with ‘sales_invoice_comment’
-- ‘sales_flat_invoice_grid’ was replaced with ‘sales_invoice_grid’ (the structure was
changed)
-- ‘sales_flat_invoice_item’ was replaced with ‘sales_invoice_item’ (the structure was
changed)
14. 6 - (Sale) Orders, Quote, Invoices, Payments,
Shipments, Bestseller info, Rules & Coupons
7. Sales Shipments
-- ‘sales_flat_shipment’ was replaced with ‘sales_shipment’
-- ‘sales_flat_shipment_comment’ was replaced with ‘sales_shipment_comment’
-- ‘sales_flat_shipment_grid’ was replaced with ‘sales_shipment_grid’ (the structure
was changed)
-- ‘sales_flat_shipment_item’ was replaced with ‘sales_shipment_item’
-- ‘sales_flat_shipment_track’ was replaced with ‘sales_shipment_track’
8. In the `sales_invoice_item` table, Magento 2 changed the method to save value of
the `weee_tax_applied` field to database: serialize() -> json_encode() function.
9. In the `sales_shipment_item` table, the `weight` field has max length 12 chars
15. 6 - (Sale) Orders, Quote, Invoices, Payments,
Shipments, Bestseller info, Rules & Coupons
10. Sales Credit Memo: Name of tables was changed (the string “_flat” was deleted)
-- The `sales_creditmemo_grid` table: some new fields and value are required in
Magento 2 like ‘updated_at’, ‘customer_name’
-- In the `sales_creditmemo_item` table, Magento 2 changed the method to save the
value of `weee_tax_applied` field to database: serialize() -> json_encode() function.
16. 6 - (Sale) Orders, Quote, Invoices, Payments,
Shipments, Bestseller info, Rules & Coupons
11. Sales Rules: Sales Rules Models Class Name changes:
-- The ‘salesrule/rule_condition_product_found’ was replaced with
‘MagentoSalesRuleModelRuleConditionProductFound’
-- The ‘salesrule/rule_condition_product_subselect’ was replaced with
‘MagentoSalesRuleModelRuleConditionProductSubselect’
-- The ‘salesrule/rule_condition_product_combine’ was replaced with
‘MagentoSalesRuleModelRuleConditionProductCombine’
-- The ‘salesrule/rule_condition_product’ was replaced with
‘MagentoSalesRuleModelRuleConditionProduct’
-- The ‘salesrule/rule_condition_combine’ was replaced with
‘MagentoSalesRuleModelRuleConditionCombine’
-- The ‘salesrule/rule_condition_address’ was replaced with
‘MagentoSalesRuleModelRuleConditionAddress’
17. 6 - (Sale) Orders, Quote, Invoices, Payments,
Shipments, Bestseller info, Rules & Coupons
12. Magento 2 added new tables for sales data ‘sales_sequence_meta’ and
‘sequece_tables’ (default table in a clean Magento installation). Magento 2 will
automatically generate ‘Sequence_tables’ related to ‘sales_sequence_meta’ (for
instance: “sequence_invoice_0, sequence_order_0…)
18. 7 - Catalog Rules
Catalog Rule Model Class Name changes:
-- The ‘catalogrule/rule_condition_combine’ was replaced with
‘MagentoCatalogRuleModelRuleConditionCombine’
-- The ‘catalogrule/rule_condition_product’ was replaced with
‘MagentoCatalogRuleModelRuleConditionProduct’
-- The ‘catalogrule/rule_action_collection’ was replaced with
‘MagentoCatalogRuleModelRuleActionCollection’
19. View graphic in full size:
[Infographic] Magento 1 vs Magento 2
Database Structure
https://www.ubertheme.com/magento2/infographic-magento-1-vs-magento-2-
database-structure/
20. 8 - RESOURCES
1. UB Data Migration Pro tool for Magento 2:
https://www.ubertheme.com/magento-news/magento-2-data-migration-pro-
release/
2. Tutorial Video - Migrate Magento 1 to Magento 2:
https://youtu.be/Jvr8d3OeB8M
21. You might be interested in our new Magento 2 releases.
For more details, head over to www.ubertheme.com
or reach us via info (at) ubertheme.com