1. Oracle 12c, 18c, Now 19c! OH MY! What are the Changes?
Welcome
Oracle 12c, 18c, Now 19c! OH MY! What are the Changes?
Janis Griffin
Senior Sales Engineer

2. Who Am I 11/18/2019 Senior Sales Engineer / DBA
Twitter®
Current – 30+ Years in Oracle®, DB2®, ASE, SQL Server®, MySQL®
DBA and Developer
Specialize in Performance Tuning
Review Database Performance for Customers Common Question – How do I tune it?

3. Agenda Oracle 12 Release Family – 12c, 18c, & 19c What’s changed?
Overview of releases
What’s changed?
Multitenant Architecture
SQL, Dictionary, and Optimizer Enhancements
In-Memory Column Store Option
New Partitioning Features
Sharding Capabilities

4. Oracle 12 Release Family Releases & Dates 12.1.0.1 12.1.0.2 12.2.0.1
July 2013
July 2014
September 2016 (cloud)
March 2017 (on-prem)
18.1.0
February 2018 (cloud)
Oracle announces yearly releases – changing version to include year
18.3.0
July 2018 (on-prem)
19c
GA in 2019 Q2
Expected to be final release of Oracle 12 family

5. Multitenant Architecture
12.1 Oracle’s first major architectural change since v6
Changed from non-container databases to container database (CDB)
Root database which holds Oracle’s metadata
Contains multiple pluggable databases (PDB)
Up to 253 including the seed database
Remote copy of PDB – source PDB had to be read only
12.2 Allowed for 4096 PDBs per CDB
Can create hot clone of PDB via command line
Requires local undo
Undo can now exist in PDB
Can create refreshable PDB (for VLDBs)
Had to stay in read only mode
Can relocate PDBs to different CDBs online
Can help maintain SLAs for performance and availability

6. Multitenant Architecture
© 2016 SOLARWINDS WORLDWIDE, LLC. ALL RIGHTS RESERVED.

7. Multitenant Architecture
12.2 – cont.
Can set INMEMORY_SIZE at each PDB
Can flashback a single PDB
FLASHBACK PLUGGABLE DATABASE pdb1 TO TIMESTAMP some_date;
Data Guard now supports individual PDB-level failover
Can set parameter ENABLED_PDBS_ON_STANDBY on standby database
Examples – ‘*’, ‘PDB?’, ‘PDB*’, ‘-PDB1’
18c – AKA
DBCA can clone local PDB (plugged)
Silent example: shell>./dbca –silent –createpluggabledatabase –sourcedb cdb1 –
shell> createpdbfrom pdb1 –pdbName pdb1_clone –sourcepdb pdb1
Refreshable PDB switchover allows replicas to go from read-only to read-write

8. Refreshable PDB
12.2
18c

9. Multitenant Architecture
18c – cont.
Further integration with Data Guard
Snapshot Carousel
Can maintain 8 point-in-time snapshots
CDB Fleet
Is a group of CDBs that can be managed from 1 lead CDB
Simplifies management

10. 18c Snapshot Carousel & CDB Fleet

11. Multitenant Architecture
19c is the Long Term Support version
Primary support to 2023, extended to 2026
Future features
Main focus is on bug fixes & stability
Trying to deprecate non-CDB databases in next (20c) release
Should allow for Real Application Testing (RAT)
and Automatic Database Diagnostic Monitor (ADDM) at PDB level

12. Agenda Oracle 12 Release Family – 12c, 18c & 19c What’s changed?
Overview of releases
What’s changed?
Multitenant Architecture
SQL, Dictionary, and Optimizer Enhancements
In-Memory Column Store Option
New Partitioning Features
Sharding Capabilities

13. SQL, Dictionary, and Optimizer Enhancements
12.1
FETCH FIRST n ROWS ONLY
Retrieves first rows without scanning everything
OFFSET n ROWS FETCH FIRST n ROWS ONLY
Skip some number of rows

14. New SQL – Cont. 12.2 Approximate Query Processing
Used for approximate ‘count distinct’ values and adds percentile aggregation
Allows for faster processing of large data sets
Not exact but usually within 95%+ range
Three new parameters – alter system/session
approx_for_aggregation - Default=FALSE
Can be overridden by the next 2 parameters
If true, sets approx_for_percentile=ALL
approx_for_count_distinct - Default=FALSE
Overrides exact COUNT DISTINCT clause
approx_for_percentile - Default=NONE
Overrides MEDIAN clause (PERCENTILE_CONT)
Values can be PERCENTILE_CONT, PERCENTILE_DISC, and ALL
Can be used without any changes to existing code

15. New SQL Functions 12c Approximate Query Functions – cont.
APPROX_COUNT_DISTINCT (Introduced in 12.1)
APPROX_COUNT_DISTINCT_DETAIL
APPROX_COUNT_DISTINCT_AGG
TO_APPROX_COUNT_DISTINCT
APPROX_MEDIAN
APPROX_PERCENTILE
APPROX_PERCENTILE_DETAIL
APPROX_PERCENTILE_AGG
TO_APPROX_PERCENTILE
Support for Materialized Views and Query Rewrite
VALIDATE_CONVERSION
Simplifies coding for input validation

16. 12c Approximate SQL Example
95% accurate

17. Using 12c Approximate Without Code Change
Why is it still exact?
Need to set both

18. 12c Approximate Percentile – No Code Change
99.68% accurate

19. New SQL Functions 18c Approximate Top-n Query Processing APPROX_RANK
Must be used in conjunction with APPROX_SUM or APPROX_COUNT
Can’t get bottom-n queries
Requires ORDER BY DESC clause
APPROX_SUM
APPROX_COUNT
Complete list - Aggregate Functions
New DBMS_SLEEP function suspends session for ‘n’ number of seconds
Needs no extra privileges
Replaces DBMS_LOCK

20. 18c New SQL Functions Examples
Approximate Sum/Rank
Actual

21. Dictionary Improvements
Object identifiers have increased from 30 bytes to 128 bytes
Such as users, roles, tables, columns, indexes, constraints, etc…
May affect your metadata reporting if report not formatted
Exceptions:
Disk groups, pluggable databases (PDBs), rollback segments, and tablespaces
Still 30 bytes
Names of databases are still limited to 8 bytes
18c
New SHARDS() clause on dictionary tables
Can be used to query across all shards
Ability to encrypt credential data instead of obfuscate
SYS.LINK$ and SYS.SCHEDULER$_CREDENTIAL
ALTER DATABASE DICTIONARY
19C
More Data Dictionary encryption capabilities
SELECT ora_shard_id, count(*)
FROM shards(v$sql)
GROUP BY ora_shard_id;

22. SQLPLUS Improvements 12c HISTORY SET STATEMENTC[ACHE] {0 | n}
SET HIST[ORY] {ON | OFF | n}
SET STATEMENTC[ACHE] {0 | n}
SET FEEDBACK ONLY
Instead of just [ON | OFF]
Sqlplus
Sets ARRAYSIZE 100, LOBPREFETCH 16384,
PAGESIZE 50000, ROWPREFETCH 2,
STATEMENTCACHE 20
Make its run faster
Can create CSV format
SET MARK CSV ON [DELIMI{TER} character] [QUOTE {ON|OFF}]

23. SQLPLUS Improvements 18c 19c SET LINESIZE WINDOW
SET FEEDBACK ON SQL_ID
SET ROWLIMIT n
19c
EZConnect Improvements
Accepts list of name value pairs
sqlplus transport connect_timeout=30&retry_count=4

24. Optimizer Changes 12c – New Adaptive Optimizer
New init.ora parameters (12.2)
OPTIMIZER_ADAPTIVE_PLANS (Default = TRUE)
OPTIMIZER_ADAPTIVE_STATISTICS (Default = False)
Obsolete – OPTMIZER_ADAPTIVE_FEATURES
Used in 12.1
New DBMS_STATS preference
AUTO_STAT_EXTENTIONS
Default is OFF
Optimizer_dynamic_sampling
New Level 11 (Auto)
New optimizer statistics advisor

25. Optimizer Changes 18c – Autonomous Database Oracle’s cloud offering
Specialized by 2 different workloads
ADW
Data mart
Data lake
Machine learning
Optimizations
Columnar format
Create data summaries
Parallel joins and aggregations
Statistics updated in real-time – prevents plan regressions
ATP
OLTP/Batch
Reporting
Application development
IoT
Machine learning
Row format
Data caching to avoid I/O

26. 18c Autonomous Database Benefits
Spend less time
Eliminate tedious manual database management tasks
Automation reduces errors
Spend less $$$
Oracle claims to cut runtime costs up to 90%
With pay-per-use and ultra-efficiency
Develop new applications faster
With instant database provisioning and self-tuning
Ensure data safety
Continuous online updates to product against cyber-attacks
Fault-tolerant solution – including maintenance

27. 18c Scalable Sequences & Private Temporary Tables
In order to solve contention in RAC environments
Sequences can be scalable by adding extra numbers
Extra 6 digits = 3 instance number offset + 3 session number offset
Scale = 6 digits + normal sequence number
Extend = 6 digit + max value
Private temporary tables
Stored in memory and only visible to session
Dropped after session or transaction
Tables must be prefixed with ORA$PTT_
Controlled by parameter
PRIVATE_TEMP_TABLE_PREFIX
create private temporary table ORA$PTT_tmp_table (id number, desc varchar2(30))
on commit drop definition; OR on commit preserve definition;

28. 18c Automatic Fixes For Runaway SQL Statements
Manage runaway sql statements on ATP using the Service Console
Controlled by resource manager via rules
Select Consumer group: TPURGENT, TP, HIGH, MEDIUM, or LOW
Set runaway criteria values
Query run time (seconds)
Amount of I/O (MB)
Can use procedure cs_resource_manager.update_plan_directive
If consumer runs more than time or I/O specified
SQL statement is killed
BEGIN
cs_resource_manager.update_plan_directive(consumer_group => 'HIGH', io_megabytes_limit => 1000, elapsed_time_limit => 120);
END; /

29. Optimizer Changes 19c Automatic Indexing
Implements indexes based expert index tuning knowledge
Without DBA involvement
Except for
DBA can set preferences
View report of indexes and their impact on the application
Works incrementally
So needs to be iterative and continuous
Automatic indexes are validated
Then adapt to changes in schema, data and application

30. 19c Automatic Indexing High Level Steps
No DBA interaction
All tuning activities
Auditable via reporting
Verify
Identify
Decide
Capture
Monitor
Online Validation

31. 19c Automatic Indexing – How It Works
Capture
Captures the application SQL history into a SQL repository
Includes SQL, plans, bind values, execution statistics, etc.
Identify Candidate Indexes
That may help the newly captured SQL statements
Creates indexes as unusable invisible indexes
Metadata only
Drops indexes obsoleted by newly created indexes (logical merge)
Verify
Ask optimizer if index candidates will be used for captured SQL statements
Materialize indexes and run SQL to validate that performance improved
All verification is done outside application workflow
Verify
Identify
Decide
Capture
Monitor
Online Validation

32. 19c Automatic Indexing – How It Works
Decide
If performance is better for all statements, indexes are marked visible
If performance worse for all statements, indexes remain invisible
If performance worse for some statements
Indexes are marked visible except for SQL statements that regressed
Online Validation
Validation of new indexes continues for other statements online
Only one of the sessions executing a SQL statement
is allowed to use the new indexes
Monitor
Index usage is continuously monitored
Automatically created indexes will be dropped if not used in a long time
Verify
Identify
Decide
Capture
Monitor
Online Validation

33. 19c Automatic Indexing Benefits
Great for OLTP, OLAP, mixed workloads but critical for OLTP
Applies to tuned and un-tuned applications
If tuned
Existing secondary indexes may be outdated
Important indexes are missing
Some secondary indexes can be dropped and auto indexes can be added
If un-tuned
Existing indexes support primary and unique key constraints
Can be used in all stages of application lifecycle
Support single and concatenated indexes
Function-based indexes
Compression advanced low
Verify
Identify
Decide
Capture
Monitor
Online Validation

34. 19c Automatic Indexing
Automatic indexing defaults to run in same database as application
Indexing task consumes CPU, memory and storage
Resource manager plan limits task to 1 CPU
DBA can control
Which temp tablespace is used to build indexes
Which tablespace and how much space can be used by auto indexing
Production Database
CPU Task
Memory Build
Storage Store

35. 19c DBMS_AUTO_INDEX Controls Auto Indexing
Automatic indexing parameters
AUTO_INDEX_EXCLUDE_SCHEMA
Holds schema names(s) to be exclude from auto indexing
Default is all tables in all user created schemas
AUTO_INDEX_RETENTION_FOR_AUTO
Number of days (default 373) auto indexes retained after last used date
AUTO_INDEX_RETENTION_FOR_MANUAL
Number of days (default NULL) manual indexes retained after last used date
AUTO_INDEX_DEFAULT_TABLESPACE
Tablespace name where auto indexes will be stored (user default tablespace)
AUTO_INDEX_MODE
Put automatic indexing into reporting mode (default=implement)
Indexes are created, tested, and a report shows the impact without affecting the app

36. 19c Automatic Indexing Views
DBA_AUTO_INDEX_EXECUTIONS
Shows history of automatic indexing tasks executions
DBA_AUTO_INDEX_STATISTICS
Shows statistics related to automatic indexes
DBA_AUTO_INDEX_IND_ACTIONS
Shows actions performed on automatic indexes
DBA_AUTO_INDEX_SQL_ACTIONS
Shows actions performed on SQL to verify automatic indexes
DBA_AUTO_INDEX_CONFIG
Shows history of configuration settings related to automatic indexes

37. 19c Automatic Indexing Reporting & Hints
Each auto index task generates a report
Reports can be generated via
DBMS_AUTO_INDEX.REPORT_ACTIVITY function
Date/Time range
Format (XML, HTML, Text)
Level (basic, typical, all)
Section
Summary, Index Details,
Verification Details, Errors, All
Test_Drive_Auto_Index_Creation
Use hints to control auto indexes
/*+ USE_AUTO_INDEXES */
/*+ NO_USE_AUTO_INDEXES */

38. 19c Statistics Management & DBMS_XPLAN
Historically, statistics gathering could cause issues
If performed daily, they could become too stale
If dynamic, they may cause too much parsing (CPU) activity
High frequency automatic statistics task
Some gathering is done during the day when system is idle
Controlled by Resource Manager
Real-time statistics
Some statistics such as high/low values are maintained during DML
DBMS_XPLAN
Reports hint usage (18c)
Per operation and alias name
Shows hints that were not used and why
Improved compare plans (19c)

39. Agenda Oracle 12 Release Family – 12c, 18,c & 19c What’s changed?
Overview of releases
What’s changed?
Multitenant Architecture
SQL, Dictionary, and Optimizer Enhancements
In-Memory Column Store Option
New Partitioning Features
Sharding Capabilities

40. 12c In-Memory Option Transactions in Buffer Cache
Analytics in In-Memory Column Store

41. IM – Why Use it? Access only the column data needed
Can prioritize when IM is populated
Partially load some columns at startup
Load other columns when accessed
ALTER TABLE customers INMEMORY PRIORITY CRITICAL;
In compressed format
Saves space
Can scan or filter compressed data
Only decompressed when used in the result set
CREATE TABLE test (c1 NUMBER, c2 NUMBER, c3 CLOB)
INMEMORY MEMCOMPRESS FOR QUERY NO INMEMORY(c3),
INMEMORY MEMCOMPRESS FOR CAPACITY HIGH (c2);
DBMS_COMPRESSION (advisor)
Now supports IM compression

42. IM – Why So Fast
IM is made up of multiple In-Memory Compression Units (IMCUs)
Background worker processes allocate their own IMCUs
Works with the IMCO (In-Memory Coordinator) background process
Uses SIMD Vector processing
Definition: Single Instruction processing Multiple Data values
Allows a set of column values to be evaluated simultaneously in one CPU instruction
Look at V$STATNAME
‘IM scan CUs columns accessed’,   'IM scan segments minmax eligible',  'IM scan CUs pruned');
New in 12.2 – IM FastStart
Allows for checkpoint of IMCUs to FastStart area on disk
Takes up storage space but less CPU intensive on startup
Best for queries that scan large amounts of data or compute values on the fly
BEGIN
dbms_inmemory_admin.faststart_enable('FS_TBS');
END;

43. *IM – Why So Fast IM Storage Indexes
Automatically created and maintained on each column in the column store
Allows pruning to occur based on filter predicates in the query
Keeps track of min/max values for each column in an IMCU
Helps to avoid scans of IM column store
New in In-Memory Expressions
Materialize commonly used expressions
Prevents re-computation for every row
Are derived values that take advantage of IM
Expression Statistics Store(ESS) automatically stores top 20 popular expressions
Manage with DBMS_INMEMORY_ADMIN package
Set with INMEMORY_EXPRESSIONS_USAGE parameter
In-Memory Virtual Columns
Needs INMEMORY_VIRTUAL_COLUMNS parameter set to ENABLED or MANUAL

44. IM - How To Use It
IM column store is disabled by default (requires restart)
Set INMEMORY_SIZE parameter to enable
Needs to be set to 100mb or higher
New in Can increase on the fly at 128mb or higher
Part of SGA - may need to increase SGA_TARGET / MEMORY_TARGET

45. IM – How To Use It
Objects must have the INMEMORY attribute to use the IM column store
Can be tablespace, table, (sub)partition or materialized view
To view objects in column store
– see V$IM_SEGMENTS, V$IM_COLUMN_LEVEL, any V$IM% views

46. IM Performance
No IM

47. *IM Virtual Columns Example – New 12.2 Feature
alter system set inmemory_virtual_columns = ENABLE;

48. *IM Joins In-Memory Joins Bloom Filters (10g)
Transforms join into a filter if there are filtering predicates
Can be used in column format via SIMD vector processing
New in 12.2 – Join Groups
Can be used when there are no filtering predicates
Allow join columns from multiple tables to share a single compression dictionary
Hash joins don’t have to decompress the data first
View join groups in USER_JOINGROUPS
View shared dictionary in v$IM_SEGDICT
CREATE INMEMORY JOIN GROUP jgroup_name(order_item(ol_i_id),item(i_id));

49. *IM Join Group Example – Cont.
SELECT ol_o_id,ol_number, ol_delivery_d, i_name, i_price
FROM order_item, item
WHERE ol_i_id = i_id and i_price < 2.00;
Join Groups share the same compression dictionary
This allows for joins to occur on compressed values
Doesn’t need to decompress and hash the data
Join columns above are order_item.ol_i_id and item.i_id
Tables need to be reloaded after the Join Group creation
To create the common compression dictionary, called Global Dictionary
Ensure the Global Dictionary exists by checking V$IM_SEGDICT_GD
SELECT o.object_name table_name,
c.column_name column_name,
gd.head_address "GD Address"
FROM user_objects o,
user_tab_columns c,
v$im_segdict gd
WHERE gd.objn = o.object_id
AND o.object_name = c.table_name
AND gd.column_number = c.column_id;

50. *IM Join Group Example – New 12.2 Feature
Using Bloom Filter / Join Group?
No IM

51. *IM Join Group Example Finding join group usage
Need to use SQL_MONITOR - dbms_sqltune.report_sql_monitor_xml or OEM
Query needs ‘SELECT /*+ MONITOR */’ hint
Columnar encodings leveraged = 1
Columnar Encodings Leveraged

52. 18c IM New Features Dynamic capture window for IM expressions
Prior releases could specify last 24 hours or since database creation
Now can specify flexible / dynamic intervals
Allows change for different workloads
Automatic IM management
New parameter: inmemory_automatic_level
Uses heat map data, column stats and other stats to manage IM objects
Evicts inactive segments if frequently accessed segments would benefit
Prior releases: difficult to know which segment would benefit
While Memory Advisor is helpful, actual usage is best

53. 18c IM New Features IM Support for external tables (100x faster)
Great feature for analytical queries on external data stores.
Avoids unnecessary access to external storage
LOBs can now be used with IM
Increases LOB performance
IM optimized arithmetic
New IM format for numbers (40x faster)
IM dynamic scans (2x faster)
Enable dynamic parallel execution of IM table scans
Prior releases used traditional parallel execution
Now dynamic scans adjust according to CPU utilization
Parallelize operations with and across IMCUs

54. 18c IM New Features Memoptimized rowstore 19c IM Features
Fast lookup for tables queried often by primary key
Internet of Things (IoT)
New area in SGA = MEMOPTIMIZE_POOL_SIZE
Create or alter table with ‘memoptimize for read’ clause
Requires NOT DEFERRABLE PRIMARY KEY constraint
19c IM Features
Faster ingest support for IoT
To stream data continuously to database
Inserts buffered in memory
Written asynchronously with bulk inserts
Database_In_Memory-P.pdf

55. Agenda Oracle 12 Release Family – 12c, 18,c & 19c What’s changed?
Overview of releases
What’s changed?
Multitenant Architecture
SQL, Dictionary, and Optimizer Enhancements
In-Memory Column Store Option
New Partitioning Features
Sharding Capabilities

56. 12.2 Partitioning Features
Read-only partitions
Useful for old partitions
Use READ ONLY
READ WRITE (default)
Can use CTAS or ALTER
Alter table move partition
Online
Alter table split partition

57. 12.2 Partitioning Features
Convert Non-partitioned table
To a partitioned table ONLINE
UPDATE INDEXES clause is optional. Indexes with SYS names will be generated if not used.

58. 12.2 Partitioning Features
Automatic List Partitions
Requires creation of first partition
No default partitions
Multi-column List Partitions
Can have only one default partition

59. 18c Partitioning Features
Online merging of partitions / subpartitions
More online modify partition features
19c Partitioned hybrid tables
Can have different partiton types – Heap or External
Roadmap-Praesentation.pdf

60. Agenda Oracle 12 Release Family – 12c, 18,c & 19c What’s changed?
Overview of releases
What’s changed?
Multitenant Architecture
SQL, Dictionary, and Optimizer Enhancements
In-Memory Column Store Option
New Partitioning Features
Sharding Capabilities

61. 12.2 Sharding Feature
Sharding horizontally partitions data across independent databases
A ‘share nothing’ architecture – CPU, memory, disk
Each database is known as a shard
All shards together make up a logical database
Called sharded database (SDB)
System-managed or composite sharding methods
Intended for custom OLTP applications that:
Have a well-defined data model
Have a data distribution strategy
(consistent hash, range, list, or composite)
Primarily access data using a sharding key
e.g., customer_id, account_no, or country_id

62. 12.2 Sharding Feature Benefits of Sharding Companies Examples
Linear scalability for performance and capacity
Eliminates single points of failure
Nothing is shared
Geographical distribution of data
Data is closer to consumers (e.g. Facebook)
Satisfies regulatory requirements
Simplifies Cloud Deployment
Easy to do rolling upgrades
Companies Examples
Online payment systems
Regulatory requirements
Airline ticketing systems
Social media companies

63. SDB Components Shard Catalog Shard Directors Global service
An Oracle database that centralizes management of a SDB
Supports automated shard deployment
Handles multi-shard queries
Holds master copy of duplicated table
Shard Directors
Network listeners which route connections based on a sharding key
Connection pools can act as shard directors for pooled connections
Global service
An extension of database services for the SDB
Management Interfaces
GDSCTL (command-line utility) and OEM

64. SDB Architecture
To install, download Oracle Database 18c (18.3) for Linux(18.3) for Linux:
linux.x64_180000_db_home.zip Oracle Database 18c Global Service Manager (GSM/GDS) : linuxx64_12201_gsm.zip

65. 18c Sharding Features User-defined Sharding RAC Sharding
Allows partitioning by RANGE or LIST
User can explicitly map data to specific shards
Has full control on moving data between shards
RAC Sharding
Logically enables affinitized table partitions to RAC instances
Reduces block pings across instances
Yields better cache affinity
Gives the performance and scalability of a sharded database
To enable
Alter system enable affinity <tablename>;
No changes to database schema are required
No need to deploy sharding infrastructure

66. 18c Sharding Features Midtier Sharding
oraclesharding-whitepaper pdf
Midtier Sharding
Ability to affinitize midtiers with shards
Eliminates requirement of each connection pool
Having to connecting to all shards
18c has ‘swim lanes’
Application tier and web tier are sharded as well
Oracle provides a topology server with REST API
Provides better fault tolerance, scalability and reduce connections

67. 19c Sharding Features Support multiple PDB-Shards in same CDB
Can co-exist with other non-sharded PDBs
Benefits are consolidation of shards, manage many as one, upgrades, etc.
Scale-out multi-shard query coordinators
Can configure shard catalog's ADG standbys
To act as multi-shard query coordinators
Great for analytic workloads that need to query multiple shards
Multiple Table Families
Allows sharded database to support multiple table families,
Each can be sharded with a different sharding key
Generation of globally unique sequence numbers across shards
For non -primary key columns (e.g. order_id)

68. How to Test 19c Oracle Live SQL Livesql.oracle.com
Can save scripts and share
Available code library
Available sample schemas

69. Summary
Oracle 12c family – first major architectural release since Oracle 6
Many new changes to 12c, 18c – now 19c
New Multitenant Architecture
SQL, Dictionary, and Optimizer Enhancements
Adaptable optimizer
Automatic indexing
In-Memory Column Store Option
Must faster for analytical queries
New Partitioning Features
Many robust online features
Sharding Capabilities
The global database that’s highly available and scalable