Highly Scalable
AUGUST 20, 2013
The shortcomings and drawbacks of batch-oriented data processing were widely recognized by the Big Data community quite a long time ago. The engine should be compact and efficient, so one can deploy it in multiple datacenters on small clusters. High performance and mobility. Pipelining.
Dynatrace
DECEMBER 15, 2022
Besides the traditional system hardware, storage, routers, and software, ITOps also includes virtual components of the network and cloud infrastructure. Although modern cloud systems simplify tasks, such as deploying apps and provisioning new hardware and servers, hybrid cloud and multicloud environments are often complex.
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The Morning Paper
MAY 14, 2019
Seer: leveraging big data to navigate the complexity of performance debugging in cloud microservices Gan et al., When a QoS violation is predicted to occur and a culprit microservice located, Seer uses a lower level tracing infrastructure with hardware monitoring primitives to identify the reason behind the QoS violation.
ACM Sigarch
MAY 31, 2023
Heterogeneous and Composable Memory (HCM) offers a feasible solution for terabyte- or petabyte-scale systems, addressing the performance and efficiency demands of emerging big-data applications. Jason Lowe-Power (UC Davis) discussed smart memory management and the need for an efficient interface for it.
Scalegrid
MAY 13, 2020
Greenplum Database is an open-source , hardware-agnostic MPP database for analytics, based on PostgreSQL and developed by Pivotal who was later acquired by VMware. Greenplum’s high performance eliminates the challenge most RDBMS have scaling to petabtye levels of data, as they are able to scale linearly to efficiently process data.
Percona
JANUARY 19, 2023
For instance, in Percona Managed Services , we have many clients with TBs worth of data that are well performant. In this blog post, we will review key topics to consider for managing large datasets more efficiently in MySQL. InnoDB will sort the data in primary key order, and that will serve to reference actual data pages on disk.
Scalegrid
FEBRUARY 8, 2024
Key Takeaways Distributed storage systems benefit organizations by enhancing data availability, fault tolerance, and system scalability, leading to cost savings from reduced hardware needs, energy consumption, and personnel. This strategy reduces the volume needed during retrieval operations.
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