Dynatrace

FEBRUARY 15, 2023

Additionally, its modern architecture delivers cost-effective storage and compute. As a result, teams benefit from low-cost cloud storage that provides access to all data and doesn’t require data rehydration. Teams can visualize an application’s vital signs, including its security posture. Site Reliability Guardian.

Analytics 130

Analytics Storage Cloud Code 130

Dynatrace

NOVEMBER 4, 2022

Overall, 53% of IT leaders say t he number of tools needed to monitor the end-to-end technology stack makes it difficult to operate efficiently. Complex and quick: The data explosion challenge . When issues arise, teams can’t depend on these tools for quick resolutions, because data comparisons are difficult and contribute to delays.

Government 147

Government Analytics Cloud Storage 147

Dynatrace

SEPTEMBER 30, 2021

Major cloud providers such as AWS offer certification programs to help technology professionals develop and mature their cloud skills. Not only will they get much more out of the tools they use daily, but they’ll also be able to deliver superior functionality, efficiency, and performance to your customers. Data analytics.

AWS 205

AWS Best Practices Analytics Cloud 205

Scalegrid

DECEMBER 6, 2023

ScaleGrid’s comprehensive solutions provide automated efficiency and cost reduction while offering tailored features such as predictive analytics for businesses of all sizes. All the tedious tasks such as storage, backups, and configuration are managed by an attentive crew so that you can concentrate on making your vacation special.

Database 130

Database Cloud Hardware Storage 130

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . Because IMDGs have highly scalable storage capacity, they can easily return large numbers of matching objects to the client application, and this leads to network bottlenecks transferring large amounts of data from the IMDG back to the client.

Analytics 52

Analytics Airlines Cache Scalability 52

ScaleOut Software

JULY 21, 2020

ScaleOut StateServer® Pro Adds Analytics to In-Memory Data Grids . Because IMDGs have highly scalable storage capacity, they can easily return large numbers of matching objects to the client application, and this leads to network bottlenecks transferring large amounts of data from the IMDG back to the client.

Analytics 52

Analytics Airlines Cache Scalability 52

Dynatrace

DECEMBER 15, 2022

In this blog, we share three log ingestion strategies from the field that demonstrate how building up efficient log collection can be environment-agnostic by using our generic log ingestion application programming interface (API). In the “Storage and Logging” section, select “ awsfirelens ” as the log driver.

Strategy 177

Strategy AWS Open Source Transportation 177

ScaleOut Software

JULY 19, 2021

Real-Time Device Tracking with In-Memory Computing Can Fill an Important Gap in Today’s Streaming Analytics Platforms. The Limitations of Today’s Streaming Analytics. How are we managing the torrent of telemetry that flows into analytics systems from these devices? The list goes on.

IoT 78

IoT Analytics Big Data Architecture 78

Percona

JUNE 4, 2023

MariaDB retains compatibility with MySQL, offers support for different programming languages, including Python, PHP, Java, and Perl, and works with all major open source storage engines such as MyRocks, Aria, and InnoDB. Efficient data processing and indexing, making it optimal for executing queries and handling large datasets.

Open Source 52

Open Source Servers Storage Scalability 52

Percona

MARCH 30, 2023

Further, open source databases can be modified in infinite ways, enabling institutions to meet their specific needs for data storage, retrieval, and processing. Non-relational databases: Instead of tables, non-relational (NoSQL) databases use document-based data storage, column-oriented storage, and graph databases.

Open Source 77

Open Source Database Storage Scalability 77

ScaleOut Software

JANUARY 9, 2020

To keep operations efficient and cost-effective, it’s important to be able to quickly respond to issues as they occur and efficiently verify their resolution. In addition, the platform provides fast, in-memory data storage so that the application can easily and quickly record both telemetry and analytics results for each store.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

To keep operations efficient and cost-effective, it’s important to be able to quickly respond to issues as they occur and efficiently verify their resolution. In addition, the platform provides fast, in-memory data storage so that the application can easily and quickly record both telemetry and analytics results for each store.

Logistics 52

Logistics Retail Analytics Azure 52

ScaleOut Software

JANUARY 9, 2020

To keep operations efficient and cost-effective, it’s important to be able to quickly respond to issues as they occur and efficiently verify their resolution. In addition, the platform provides fast, in-memory data storage so that the application easily can keep track of both telemetry and analytics results for each store.

Logistics 52

Logistics Retail Analytics Azure 52

HammerDB

JUNE 27, 2022

The TPC designed benchmarks for transaction processing (OLTP) and analytics (OLAP) and anyone can run these benchmarks, have them audited by the TPC and published on the official benchmark rankings. What programming languages does HammerDB use and why does it matter? Adoption by the TPC. Derived Workloads. Cached vs Scaled Workloads.

Benchmarking 62

Benchmarking Open Source C++ Cache 62

Percona

JANUARY 14, 2019

What if we use ClickHouse (which is a columnar analytical database) as our main datastore? Well, typically, an analytical database is not a replacement for a transactional or key/value datastore. However, ClickHouse is super efficient for timeseries and provides “sharding” out of the box (scalability beyond one node).

Database 40

Database Analytics Blockchain Healthcare 40

The Netflix TechBlog

MAY 21, 2019

There are several problems efficient test scheduling could help us solve: Quickly detect a regression in the integration of the Netflix SDK on a consumer electronic or MVPD (multichannel video programming distributor) device. The data can be truncated after each execution and offloaded to a long-term storage for further analysis.

Testing 163

Testing AWS Lambda Network 163

Testsigma

MAY 7, 2020

IBM Big Data and Analytics Hub website cited a case study, where a US insurance company was estimating 15% of their testing efforts to be just test data collection for the backend system and the frontend system. By Wikipedia – “Test data is data which has been specifically identified for use in tests, typically of a computer program.”.

Testing 60

Testing Storage Database Processing 60

SQL Performance

APRIL 17, 2020

With careful planning, the other steps required can be made as efficient as possible, for example using minimally-logged or ONLINE operations. Other extended events useful for tracking ALTER COLUMN operations include metadata_ddl_alter_column and alter_column_event , both in the Analytic channel. Be Careful with Syntax.

Servers 63

Servers Database Testing Efficiency 63

ScaleOut Software

MAY 4, 2014

Usually this means moving to a server with more CPU cores, greater memory capacity, and higher-end networking and storage options. Now CPU, memory, and storage resources can grow without predefined limits. At some point, scaling up becomes costly, and workloads grow beyond what even a high end server can handle.

Network 40

Network Servers Analytics Storage 40

Alex Russell

JULY 14, 2021

Here, native apps are doing work related to their core function; storage and tracking of user data are squarely within the four corners of the app's natural responsibilities. Without the ability to catch all navigations sent to the OS, users who downloaded these programs suffered frequent computing amnesia. How can that be?

Google 121

Google Mobile Engineering Internet 121

The Netflix TechBlog

MARCH 10, 2023

are stored in secure storage layers. Amsterdam is built on top of three storage layers. And finally, we have an Apache Iceberg layer which stores assets in a denormalized fashion to help answer heavy queries for analytics use cases. It is also responsible for asset discovery, validation, sharing, and for triggering workflows.

Strategy 258

Strategy Cache Analytics Storage 258

All Things Distributed

DECEMBER 13, 2016

AWS is not only affordable but it is secure and scales reliably to drive efficiencies into business transformations. GoSquared provides various analytics services that web and mobile companies can use to understand their customers' behaviors. Fraud.net is a good example of this. Fraud.net is a good example of this.

AWS 166

AWS Cloud Artificial Intelligence IoT 166

All Things Distributed

NOVEMBER 15, 2010

We believe that making these GPU resources available for everyone to use at low cost will drive new innovation in the application of highly parallel programming models. General Purpose GPU programming. But with the third generation interfaces, the true power of General Purpose GPU programming was unlocked. From CPU to GPU.

AWS 136

AWS Latency Programming Architecture 136

High Scalability

NOVEMBER 25, 2019

It is limited by the disk space; it can’t expand storage elastically; it chokes if you run few I/O intensive processes or try collaborating with 100 other users. Over time, costs for S3 and GCS became reasonable and with Egnyte’s storage plugin architecture, our customers can now bring in any storage backend of their choice.

Architecture 52

Architecture Cache Azure Storage 52