In Memory DB Presentation (Revised)

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IN-MEMORY DATABASES
Presenter #10:
Robert Vitolo
10 REASONS
Why it makes
a good option
for your DB
IN-MEMORY DATABASES SUMMARIZED
 Stores and manipulates table data within the main memory
space
 Also known as:
 MMDB (Main Memory Database)
 IMDB (In-Memory Database)
 IMDS (In-Memory Database System)
 Implemented using a large amount of memory and/or
compression schemes
 Characterized by high performance through algorithmic
simplicity and the lack of I/O operations
10 REASONS SUMMARIZED
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Real-time data processing
Usage in embedded devices
More ef ficient use of computer resources
Data-set testing in application development
Reduced development / manufacturing cost for products
Feasibility due to dropping cost of RAM
Cost ef fective alternative to data warehousing
High capacity support through compression
Flexibility through hybrid products
Support of the ACID standard
REAL TIME DATA PROCESSING
 When information is changing on a constant basis (in real time)
 Examples:
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Stock market trading
Sensor monitoring
Online auctions
Air traffic control
 Limitations of traditional DBs: lack timing constraints,
consistently high performance
 Real-time database systems utilizing an MMDB model can
ensure consistency in the data that is captured and queried
EMBEDDED DEVICES
 “Smart” devices dedicated to handle specific tasks
 Examples:
 Set-top boxes
 Cell phones: “Smart Phones”
 Rely on main memory for local storage of retrieved data
 Typically low power devices designed with modest hardware
specifications
 Absence of magnetic disks improves power performance and
MMDBs still operate faster than flash memory
EFFICIENT USE OF RESOURCES
 Traditional DB optimization has focused on enhancing speed
through improving frequent file I/O operations
 MMDBs are built from the ground up from the viewpoint of
maximizing memory performance, fewer CPU instructions
 Fewer I/O operations, no need for building large indexes, no
cache management, less code complexity
 CPU spends the bulk of it’s time working directly with data,
not managing, translating, and moving it between CPU and
disks
TESTING IN ENTERPRISE APPLICATIONS
 Manufacturers of enterprise database/server applications
need to run test suites on their software using large datasets
to identify bugs
 Utilizing an MMDB reduces build times and down time by
processing the dataset more quickly.
REDUCED DEVELOPMENT /
MANUFACTURING COSTS
 Streamlined code allows for easier development and easier
debugging and troubleshooting.
 Specialized devices like smart phones can be manufactured
for less money, as they don’t require extra disks for
redundancy and can use fewer hardware components
FALLING COST OF RAM
HARD DRIVE PRICES UP 90 – 180%
ALTERNATIVE TO DATA WAREHOUSING
 Upfront costs of hardware, servers and space make building a
data warehouse a non-starter for small to mid -sized
businesses.
 An MMDB and in-memory analytical tools provides the ability
to analyze large data sets, but is simple to setup, administer,
and maintain.
SUPPORT FOR LARGE DATABASES
THROUGH COMPRESSION
 Limitation of MMDB: Your database can only be as large as
your main memory.
 Diverted through compression: Oracle’s Exalytics product
allows up to 10TB of data in main memory per 1TB DRAM
chip.
 In the future: deal with larger databases using DIMDB
(Distributed In Memory Database) that harness the main
memory systems of several computers connected by network
or in the cloud
 Example: Network Cloud DB by Xeround
FLEXIBILIT Y THROUGH HYBRID
PRODUCTS
 Some MMDBs can be run in a hybrid mode, allowing both in memory data processing and on -disk tables.
 Examples:
 Solid DB by IBM
 Altibase
 H2
 This allows an organization to try out an MMDB without
abandoning their traditional DB structure if the hardware is
already in place, or gradually transition to a fully MMDB
solution as hardware needs to be replaced.
SUPPORT FOR ACID STANDARD
 ACID: Atomicity, Consistency, Isolation, and Durability
 Biggest strength of an MMDB is also its biggest weakness:
MMDB stores all data in volatile RAM
 Getting around it:
 NVRAM / Battery backup RAM
 Redundancy through backup to disk storage / Network
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