The document provides a metric weightage for evaluating various in-memory databases. It includes sub-metrics across various categories like storage, server type, use cases, benchmarks, integration, performance, operation, cost, and security. Each sub-metric is assigned a specific weightage based on its importance. Vendors like Oracle, SAP Hana, Kognitio, VoltDB, GridGain, MemSQL, SQLFire, and Altibase are then rated against each sub-metric to calculate a total score.
This plugin allow you to monitor McAfee ePolicy Orchestrator application. To monitor the
application the status of all services that support the application will be controlled. The monitoring
approach is based on local modules.
For more information visit the following webpage: http://pandorafms.com/index.php?sec=Library&sec2=repository&lng=en&action=view_PUI&id_PUI=277
AWS Simple Workflow: Distributed Out of the Box! - Morning@LohikaSerhiy Batyuk
Do you have a lot of complex jobs that you need to run as part of your application? Do they consist of multiple tasks and you wonder how to orchestrate them properly? Do you want to be able to easily scale their execution? Is availability of your workers important to you? If you answer “Yes” to these questions then AWS Simple Workflow is the right tool for you.
In this talk we will go through Amazon SWF and Java Flow Framework and you will see how to get a distributed job execution engine right out of the box. We will also compare SWF to alternative solutions, discuss real life experience, and of course enjoy a live demo.
The talk will be most useful to everyone who is interested in the design of distributed systems and is new to AWS SWF.
This plugin allow you to monitor McAfee ePolicy Orchestrator application. To monitor the
application the status of all services that support the application will be controlled. The monitoring
approach is based on local modules.
For more information visit the following webpage: http://pandorafms.com/index.php?sec=Library&sec2=repository&lng=en&action=view_PUI&id_PUI=277
AWS Simple Workflow: Distributed Out of the Box! - Morning@LohikaSerhiy Batyuk
Do you have a lot of complex jobs that you need to run as part of your application? Do they consist of multiple tasks and you wonder how to orchestrate them properly? Do you want to be able to easily scale their execution? Is availability of your workers important to you? If you answer “Yes” to these questions then AWS Simple Workflow is the right tool for you.
In this talk we will go through Amazon SWF and Java Flow Framework and you will see how to get a distributed job execution engine right out of the box. We will also compare SWF to alternative solutions, discuss real life experience, and of course enjoy a live demo.
The talk will be most useful to everyone who is interested in the design of distributed systems and is new to AWS SWF.
Pivotal CRM: Optimize your Pivotal ImplementationAptean
Learn how to install, configure, maintain and support a Pivotal CRM environment while following Pivotal best practices. You will receive information regarding system optimization including which components need to be monitored and what to look for while monitoring the environment.
This PPT deck displays seventeen slides with in depth research. Our Ipo Framework PowerPoint Presentation Slides presentation deck is a helpful tool to plan, prepare, document and analyse the topic with a clear approach. We provide a ready to use deck with all sorts of relevant topics subtopics templates, charts and graphs, overviews, analysis templates. Outline all the important aspects without any hassle. It showcases of all kind of editable templates infographics for an inclusive and comprehensive Ipo Framework PowerPoint Presentation Slides presentation. Professionals, managers, individual and team involved in any company organization from any field can use them as per requirement. http://bit.ly/31uDrZC
Understanding the Transaction Log, Your Key to Unlocking Greater ThroughputRichard Douglas
Does your application suffer from performance problems even though you followed best practices on schema design? Have you looked at your transaction log?
There's no doubt about it, the transaction log is treated like a poor cousin. The poor thing does not receive much love. The transaction log however is a very essential and misunderstood part of your database. There will be a team of developers creating an absolutely awesome elegant design the likes of which have never been seen before, but the leave the transaction log using default settings. It's as if it doesn't matter, an afterthought, a relic of the platform architecture.
In this session you will learn to appreciate how the transaction log works and how you can improve the performance of your applications by making the right architectural choices.
Approach For System Analysis PowerPoint Presentation SlidesSlideTeam
This PPT deck displays seventeen slides with in depth research. Our Approach For System Analysis PowerPoint Presentation Slides presentation deck is a helpful tool to plan, prepare, document and analyse the topic with a clear approach. We provide a ready to use deck with all sorts of relevant topics subtopics templates, charts and graphs, overviews, analysis templates. Outline all the important aspects without any hassle. It showcases of all kind of editable templates infographics for an inclusive and comprehensive Approach For System Analysis PowerPoint Presentation Slides presentation. Professionals, managers, individual and team involved in any company organization from any field can use them as per requirement. http://bit.ly/3bgb5Xx
본 실습은 AWS IoT Edge 구성 요소인 AWS IoT Greengrass를 이용하여 산업 현장에서 활용되는 표준 통신 프로토콜(OPC-UA)을 AWS IoT 호환 프로토콜로 변환 전처리하는 과정을 실습합니다. 이렇게 수집된 데이터는 AWS IoT Analytics 을 통해 분석 및 BI에 활용될 수 있으며, 본 실습에서는 Amazon Sage Maker를 활용하여 예지 정비 모델을 작성 및 배포하고, 추가적으로 Amazon QuickSight를 통한 시각화 구현을 목표로 합니다.
Pivotal CRM: Optimize your Pivotal ImplementationAptean
Learn how to install, configure, maintain and support a Pivotal CRM environment while following Pivotal best practices. You will receive information regarding system optimization including which components need to be monitored and what to look for while monitoring the environment.
This PPT deck displays seventeen slides with in depth research. Our Ipo Framework PowerPoint Presentation Slides presentation deck is a helpful tool to plan, prepare, document and analyse the topic with a clear approach. We provide a ready to use deck with all sorts of relevant topics subtopics templates, charts and graphs, overviews, analysis templates. Outline all the important aspects without any hassle. It showcases of all kind of editable templates infographics for an inclusive and comprehensive Ipo Framework PowerPoint Presentation Slides presentation. Professionals, managers, individual and team involved in any company organization from any field can use them as per requirement. http://bit.ly/31uDrZC
Understanding the Transaction Log, Your Key to Unlocking Greater ThroughputRichard Douglas
Does your application suffer from performance problems even though you followed best practices on schema design? Have you looked at your transaction log?
There's no doubt about it, the transaction log is treated like a poor cousin. The poor thing does not receive much love. The transaction log however is a very essential and misunderstood part of your database. There will be a team of developers creating an absolutely awesome elegant design the likes of which have never been seen before, but the leave the transaction log using default settings. It's as if it doesn't matter, an afterthought, a relic of the platform architecture.
In this session you will learn to appreciate how the transaction log works and how you can improve the performance of your applications by making the right architectural choices.
Approach For System Analysis PowerPoint Presentation SlidesSlideTeam
This PPT deck displays seventeen slides with in depth research. Our Approach For System Analysis PowerPoint Presentation Slides presentation deck is a helpful tool to plan, prepare, document and analyse the topic with a clear approach. We provide a ready to use deck with all sorts of relevant topics subtopics templates, charts and graphs, overviews, analysis templates. Outline all the important aspects without any hassle. It showcases of all kind of editable templates infographics for an inclusive and comprehensive Approach For System Analysis PowerPoint Presentation Slides presentation. Professionals, managers, individual and team involved in any company organization from any field can use them as per requirement. http://bit.ly/3bgb5Xx
본 실습은 AWS IoT Edge 구성 요소인 AWS IoT Greengrass를 이용하여 산업 현장에서 활용되는 표준 통신 프로토콜(OPC-UA)을 AWS IoT 호환 프로토콜로 변환 전처리하는 과정을 실습합니다. 이렇게 수집된 데이터는 AWS IoT Analytics 을 통해 분석 및 BI에 활용될 수 있으며, 본 실습에서는 Amazon Sage Maker를 활용하여 예지 정비 모델을 작성 및 배포하고, 추가적으로 Amazon QuickSight를 통한 시각화 구현을 목표로 합니다.
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...2023240532
Quantitative data Analysis
Overview
Reliability Analysis (Cronbach Alpha)
Common Method Bias (Harman Single Factor Test)
Frequency Analysis (Demographic)
Descriptive Analysis
Quantitative Data AnalysisReliability Analysis (Cronbach Alpha) Common Method...
Inmemory db nick kabra june 2013 discussion at columbia university
1. Metric Weightage Sub-Metrics Criteria
Sub-
Weightage
Storage Type
1.0 - SAN/NFS/Local/SSD
0.5 - SAN/Local
0.2 - SAN only
0.0 - No SAN/NFS/Local 0.1
Server type
1.0 - Any commodity Server
0.0 - Vendor appliances 4
Use Cases
1. OLTP and DSS
0.5 - OLTP or DSS
0.0 - Non OLTP nor DSS 0.1
Customer references
1 - Excellent
0.5 Good
0.2 - Average
0.0 - needs improvement 0.1
Key Characteristics To be defined 0.1
Partition type - horizontal, column store,
1 - both
0.5 - only one
0.0 - None 0.1
Manual and Documentation
1 - Excellent
0.5 Good
0.2 - Average
0.0 - needs improvement 0.1
Longevity
1.0 - 5 yr or longer
0.5 - 2 year or longer
0.2 - 1 year +
0.0 - <1 year 0.1
Training
1 - Excellent
0.5 Good
0.2 - Average
0.0 - needs improvement 0.1
Inmemory Databases comparative analysis:Ju
2. Support
1 - Excellent
0.5 Good
0.2 - Average
0.0 - needs improvement 0.2
5
Programming Language
1.0 - PLSQL/JAVA/C
0.5 - two of above
0.2 - one of above
0.0 - None 4
Query language
1.0 - ISO/IEC 9075-1:2011 or later
0.5 - earlier than ISO/IEC 9075-1:2011
0.0 - no mention to ISO/IEC 9075-1:2011 0.5
Search queries supported To be defined 0.1
Search integration To be defined 0.1
Query types supported (DDL AND DML)
1.0 - both
0.5 - one type
0.0 - None 0.1
Complex queries types supported
1.0 - fully support
0.5 - partially support
0.0 - not support 0.1
Insert, updates, deletes, appends supported
1.0 - support all 4
0.5 - support all but appends
0.0 - Not support one of insert, update,
delete 0.1
5
Hadoop
HDFS
1.0 support
0.0 - not support 0.1
MapReduce
1.0 support
0.0 - not support 0.1
Protocols supported like Rest API, Thrift, memcache
1.0 support
0.0 - not support 0.1
General Key Facts 5
Language and query 5
3. Integration with RDBMSs specifically Oracle
1.0 - fully support
0.5 - partially support
0.0 - not support 5
Any code rewrite for Oracle
1.0 - not need
0.8 - hardly needed
0.5 - needed considerblly
0.2 - Significantely needed
0.0 - Extensively needed 5
Interface ease with Oracle
1.0 - Very easy
0.5 - fairly easy
0.2 - not easy
0.0 - not possible 4.4
Integration with visualization /charting tools: Tableau,
1.0 - Can be integrated
0.0 - Cannot be integrated 0.1
Integration with graph databases
1.0 - Can be integrated
0.0 - Cannot be integrated 0.1
Search integration - Solr, ElasticSearch
1.0 - Can be integrated
0.0 - Cannot be integrated 0.1
15
Benchmarks
Insert speed
1.0 - very fast
0.5 - fast
0.2 - somewhat fast
0.0 - negligibly fast 6
Delete Speed
1.0 - very fast
0.5 - fast
0.2 - somewhat fast
0.0 - negligibly fast 6
Update Speed
1.0 - very fast
0.5 - fast
0.2 - somewhat fast
0.0 - negligibly fast 6
Integration 15
4. Query Speed (incl. full table scan)
1.0 - very fast
0.5 - fast
0.2 - somewhat fast
0.0 - negligibly fast 7
Benchmark tool / App test
1.0 - very fast
0.5 - fast
0.2 - somewhat fast
0.0 - negligibly fast 7
Possible performance issues
1.0 - No major issues expected
0.5 - Some issue expected
0.2 - major issue expected 5
Realtime download supported
1.0 - possible
0.5 posible with special treatment
0.0 - not possible 2
Real time /latency To be defined 0
Indexing
1.0 - fast
0.0 - not fast 2
Full text search 0
Rebalancing additional servers /nodes
1.0 - can be done online without impacting
active DB
0.5 - can be done online with impacting
active DB
0.0 - cannot be done 2
Sharding /horizontal scaling /auto sharding 0
Latency before sharding or backup 0
Throughput
1.0 - Can process large amount of data in a
fix time period
0.5 - Can process fair amount of data in a
fix time period
0.25 - Can processsmall amount of data in
a fix time period 2
Compression supported
1.0 - support compression
0.0 - Does not support compression 2
47
Performance 47
5. Backup/ Data Recovery
1.0 - Extensive backup/recovery function
built in
0.5 - backup/restore function built in
0.2 - Reply on 3rd party tool
0.0 - No backup/recovery function 2
Maximum capacity supported /spillover to harddisk
1.0 - Support large database up to physical
memory in a machine
0.5 - Support >200G but< 1TB DB
0.2 - Support >100G but <200G DB
0.0 - support <100G DB 2
Scalability
1.0 - capacity can be aded dynamiclly by
adding memory or cluster nodes
0.5 - capacity can be added with extensive
work
0.0 - can’t add capacity 2
Availability
1.0 - 5x9s
0.5 - 3x9s
0.2 - 2x9s 2
Fault tolerance
1.0 - hardware redundency leveraged
0.5 - some hardware redundency can be
leveraged
0.0 - no hardware redundency helps 1
SQL Focus 0
Data Replication /Snapshots - master-slace, fan-in, master-master etc.
1.0 - all features avaialble
0.5 - some features available
0.0 - no features available 2
Audit trail /lineage 0
Ease of use
1.0 - very easy to use
0.5 - easy to use
0.2 - difficult to use 2
6. Monitoring and Management
1.0 - monitoring and mgmt teafure built in
0.5 - some monitoring and mgmt teafure
built in
0.0 - very few monitoring and mgmt
teafure built in 1
14
ACID property, MVCC support
1.0 - ACID compliented and MVCC
supported
0.0 - No ACID complanted or MVCC is not
supported 1
Any SPOF and recovery options
1.0 - No SPOF
0.5 - SPOF exists but easily recoved
0.0 - SPOF exists and cannot be recovered 1
Referential integrity
1.0 - RI is available
0.0 - RI is not available 1
Updates and Revisions
1.0 - Well scheduled update and revision
cycle
0.5 - Scheduled update and revision with
long interval
0.0 - no fixed update and revision ore-set 1
4
Encryption /decryption
1.0 - Well built-in Encryption /decryption
function
0.5 - Encryption /decryption available
0.0 - No Encryption /decryption built in 1.5
Impact on performance
1.0 - Negligible impact
0.5 - noticible impact
0.0 - Significant impact 1
Operation 14
Integrity 4
7. Integration with other security products
1.0 - Integrated with multiple products
0.5 - Integrated to less than 3
0.0 - No integration 0.1
Authentication format To be defined 0.1
Authorization
1.0 - Well established authorization feature
0.5 - some authorization feature
0.0 - No authorization built in 0.1
Country /Continent security for data viewing and changesTo be defined 0.1
Data sharing allowed To be defined 0.1
3
License basis
1.0 -Not costly
0.5 - costly
0.0 - very costly 2.5
Maintenance
1.0 -Not costly
0.5 - costly
0.0 - very costly 2.5
5
Gartner Quadrant 2 Ranking
1.0 - in the latest Gartenerreport
0.5 - in past Gartener reports
0.0 - Not mented in Gartener reports 2
100 2
Total 100
Security 3
Cost 5