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http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.178.994
CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract — Continuous data stream processing systems have offered limited support for data persistence in the past, for three main reasons: First, online, real-time queries examine current streaming data and (under the assumption of no server failures) do not require access to past data; second, stable storage ...
https://streaml.io/product/platform
Streamlio Intelligent Platform for Fast Data . ... processing and stream storage to deliver performance and scalability. ... and scalable performance needed to support large numbers of topics, publishers and consumers in a single solution to avoid the complexities of siloed data. Ease of use.
http://people.csail.mit.edu/tatbul/publications/edbt09.pdf
Flexible and Scalable Storage Management for Data-intensive Stream Processing ∗ Irina Botan, Gustavo Alonso, Peter M. Fischer, Donald Kossmann, Nesime Tatbul Systems Group, Department of Computer Science, ETH Zurich {irina.botan, alonso, peter.fischer, kossmann, tatbul}@inf.ethz.ch ABSTRACT Data Stream Management Systems (DSMS) operate under ...
https://www.oreilly.com/library/view/making-sense-of/9781492042563/
How can event streams help make your application more scalable, reliable, and maintainable? In this report, O’Reilly author Martin Kleppmann shows you how stream processing can make your data storage … - Selection from Making Sense of Stream Processing [Book]
https://streaml.io/product/technology/storage
Storage that is just patched into messaging or processing technology forces compromises that impact performance, durability, and scalability. Streamlio uses Apache BookKeeper as its foundational storage system for streaming data. Apache BookKeeper is a scalable, fault-tolerant, and low-latency storage service optimized for streaming data.
https://tel.archives-ouvertes.fr/tel-01972280/file/thesis.pdf
T HESE DE DOCTORAT DE /¶INSA RENNES C OMUE U NIVERSITE B RETAGNE L OIRE E COLE D OCTORALE N ° 60 1 Mathématiques et Sciences et Technologies de l'Information et de la Communication Spécialité : Informatique « KerA : A Unified Ingestion and Storage System
http://www.vldb.org/pvldb/vol11/p1303-mai.pdf
control-plane messages into the data stream. By leveraging the ex-isting data pipeline, control messages can be streamed at low la-tency and in a scalable fashion, without requiring any ad-hoc mech-anism (§7.2). This seemingly simple approach, however, requires support from the underlying streaming infrastructure, to executeCited by: 4
https://aws.amazon.com/streaming-data/
By building your streaming data solution on Amazon EC2 and Amazon EMR, you can avoid the friction of infrastructure provisioning, and gain access to a variety of stream storage and processing frameworks. Options for streaming data storage layer include Apache Kafka and Apache Flume.
Pravega provides a new storage abstraction - a stream - for continuous and unbounded data. A Pravega stream is a durable, elastic, append-only, unbounded sequence of bytes that has good performance and strong consistency.
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