Abbreviations and acronyms

Index

Numerics

1-safe replication 117, 120

2-safe replication 31, 117–118

A

ACID (atomicity, consistency, isolation, durability) 27

active caching 42

adaptive durability 30–31, 117 ADMIN COMMAND 37

Advanced Replication 206, 209–210 ANSI X3H2 SQL CLI 17

ANSI X3H2 standard 18 application failover 140 application server 231 applications, scaling 63 array index, applying 22

asynchronous replication 35, 42, 53, 136 atomicity 6, 27, 115

active 42 catalogs 38

character data, encoding 55 checkpoint task 158, 207 checkpointing and logging 4, 19, 25 cloud computing 63

co-locating data 224

commodity hardware system 227 concurrency control xiii, 6, 12, 23, 26–28, 30

crash 214

CREATE DENSE SEQUENCE 34 CREATE SEQUENCE statement 34

B

back-end DB2 database 254 backup task 208

binary large objects (BLOB) 23 binary tree 21

Bonsai Tree 23, 188, 199, 204 B-tree

Bonsai Tree 23 main storage tree 23 variation 22

buffer pool 220 business intelligence xii

C

cache 9–10, 12, 40–42, 45–47, 49–51, 53, 55, 58–66, 142, 144–145, 151–153, 155, 177–178, 184, 194, 196–197, 199, 202, 213, 227–228, 230, 243–246, 249, 253–254, 257, 259, 264, 271

adding relational 64 object 12, 245

cache databases 10, 64 caching

D

data aging 58–59, 245

Data Definition Language (DDL) operations 213 data duplication 60–61

durability 8, 19, 25, 30, 36, 115, 117–118, 120, 136, 194, 221, 223, 240

durability levels

adaptive durability 31 strict durability 30–31, 223

E

early validation 28

enterprise hardware system 228 Enterprise Payments Platform (EPP) 243 estimator component 20

EXPLAIN PLAN FOR command 170 External Reference Entity (ERE) 128

InfoSphere CDC 10, 41–42, 47–50, 54–56, 59–61, 143–145, 148, 162, 180–181, 198, 212, 250, 253–255

configuring 255 creating instances 43 instance area 45

in-memory tables (M-table) 20, 24 iostat utility 179

isolation levels parameters 27

READ COMMITTED 29

REPEATABLE READ 30 SERIALIZABLE 30

F

failures 109–111, 114–115, 117, 120, 124–126, 129, 136–137, 144, 162–163, 205, 242 Financial Transaction Directory 243

front-end solidDB cache 254

H

HA Controller (HAC) 126 HA framework 113, 124–125 HA Manager (HAM) 127 hang 216

Home Location Register (HLR) 236

HotStandby (HSB) 19, 26, 29–30, 35, 40, 49, 58, 109–111, 129, 131–134, 136–137, 139–140, 159, 186, 194, 198, 206, 210–211, 223, 262, 267

primary servers, adaptive durability 31 replication 35

HSB link 111, 114, 124, 126–128 hsb netcopy 138, 140

hsb set primary alone command 113, 140 hsb switch 114

primary command 114 secondary command 114

Hybrid Database Transaction Workload (HDTW) 248

I

IEC/ISO 9075 SQL standard 18 impedance mismatch 12 indexes, M-tables 21

J

Java Transaction API Specification 1.1 17

JBoss Application Server 233

K

key value comparing 21

prefix-compressed 23 presorted 24

L

Largest Value Wins, conflict resolution 56

M

main storage tree 23–24

memory 26 non-persistent 25 performance 25, 29 persistent 25

pessimistic concurrency control 28 multiple cache node 47

N

netcopy 114

network bottlenecks 200 node

configuration 35, 46, 122, 137 multiple cache 47

single cache 46–47 single database 47

O

object cache 12 object store 12 ODBC command 36

on-persistent tables 25 operational data 246

optimistic concurrency control 28–29 optimizer hints 173, 187, 197

P

parallelism 60, 198 path compression 22 persistent tables 25–26

pessimistic concurrency control 28 pessimistic locking 28–29

pmon counters 148–149, 151, 155, 159–160, 162, 186, 189–190, 192, 195, 202–203, 210, 213

categories 149 gathering 148

POJOs (Plain Old Java Objects, mapping 234 PREFERRED_ACCESS connection 133

Q

152, 173, 177, 184, 188–190, 193, 197, 199, 204,

207–208, 223, 230, 250–254, 257, 261, 264

R

READ COMMITTED 29 read dominant 222

READ/WRITE SQL statement 58

S

scaling applications 63 scaling out 258 schemas 38, 267

SECONDARY ACTIVE state 113 SECONDARY ALONE state 113 Securities Exchange Reference Architecture (SXRA) 246

separation values 23 sequence_name.CURRVAL 34 sequence_name.NEXTVAL 34 serializability 27

39–43, 45–47, 50, 53, 56, 58, 60, 62, 64–66, 142, 145, 162, 164–165, 180, 211, 219, 221–222, 226, 228, 230, 243–245, 248, 250, 252, 254, 256–258, 264–265

strict durability 8, 31, 115, 117, 223

resolution rules 61 table subsets 52

sweet spot 221 switchover 114

system services component 20

T

table mappings 52 table services 20 table subsets 52

Target Wins, conflict resolution 55 TATP 236

client 239

test session 239

Telecom Application Transaction Processing See TATP

temporary tables 26, 29 throughput 193

transaction logging 4–5, 25, 30, 58, 114, 136, 184, 186, 194, 212, 222

U

ulimit -c unlimited command 216 unique key lookups 222

Universal Cache xi–xii, xiv–xv, 1, 10–12, 35, 39–43, 45–47, 50, 53, 56, 58, 60, 62, 64–66, 142–143, 145, 162, 164–165, 180, 211, 219–222, 226–230, 243–245, 248, 250, 252, 254, 256–258, 264–265

Provides low latency, high throughput, and extreme availability

Offers fully featured relational in-memory database software

Has universal cache with shared memory access

The world seems to be getting smaller and business moving much faster. To be successful in this type of environment you need instantaneous access to any information, immediate responses to queries, and constant availability, on a worldwide basis, and in a world where the volume of data is growing exponentially. You need the best resources you can get, and ones that can satisfy those needs. IBM can help.

A primary component that can affect performance is access to disk-based data. And, as data volumes grow, so does the performance impact. To improve performance, it is time to look for technology enhancements that can mitigate that impact.

IBM solidDB is powerful relational, in-memory caching software that can accelerate traditional disk-based relational database servers by caching performance-critical data into one or more solidDB in-memory database instances. This capability can enable significant performance improvements. It brings data closer to the application so you can use a faster and more efficient data access paradigm. The result? Faster delivery of information for your queries to enable faster analysis and decision-making that can give you a significant business advantage.

Have questions? Many of the answers you need are contained in this IBM Redbooks publication.

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