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Learn how Levyx is optimizing Intel hardware in financial applications. In addition, see how Levyx adds value to RocksDB and other advanced database implementations with other partners.
- Real-time persistent computing for Big Data
- Data Store applications in the financial sector
Listen in on the Levyx team's talks on Intel's podcast "Conversations in the Cloud" to hear about how Levyx's data store technology is getting applied in real-world use cases.
For over a decade, the innovations in storage hardware and data management software progressed in silos.
Levyx bridges these silos.
Agnostic system software originally designed for optimal use of solid-state storage and multi-core CPU’s, Levyx software-defined data processor solutions allow customers to fully realize the business benefits of advances in both storage hardware AND Big Data compute software.
Welcome to the Era of Persistent Dataframes
For the first time, all real-time working datasets are:
- Persisted on Flash
- Accessible by multiple users
- Replicated for high availability
- Subject to real-time updates and transactions
Enabling Analytics on Flash
Applications / Solutions
With Levyx, enterprises that are using Spark for analytics can analyze new data instantly, no more waiting
Apache Spark users can now perform analysis on Big Data working sets as they pass through the i/o stack.
By incorporating our Levyx-Spark Connector™ software, we have integrated our core engine into Apache Spark, making Spark more "Enterprise-Grade" by providing persistence to Spark data sets.
Accelerating Big Data Analytics for the Financial Services Industry
Apply Levyx to boost performance in proprietary trading; in conjunction with Kafka-Storm or Kafka-Spark to boost streaming; or risk-management and cyber-security applications.
Make Sense of Billions of Objects Being Accessed Simultaneously
Using our KV Store to ingest very large streams in a Kafka-Storm (or other analytic engine) pipeline, reducing the number of servers by ten-fold compared to conventional NoSQL methods.
Where we sit in the I/O path
Levyx's software enables input/output (I/O) intensive legacy and Big Data applications to operate in a way that is faster, simpler and cheaper.
- Faster (by over 10x) than other solutions because of its multi-core, flash-optimized, query pushdown, and patended indexing design.
- Simpler than other architectures, which make trade-offs between performance and storage tiering complexity - all data is persisted by Levyx at memory speeds.
- Cheaper because Levyx subsitutes random access memory (RAM) with less costly Flash storage (typically 10x cheaper per GB), yet achieves equivalent or greater performance using drastically fewer distributed commodity server nodes.
- One of the World's First Flash-resident Compute Engines
- High-performance, patent-pending analytics platform sits directly on Flash SSDs
- No longer bound to DRAM for “In-Memory” performance
- One of the World’s Fastest Key Values
- Benchmarked against many of the world’s fastest KVS technologies
- Typically orders of magnitude faster than the rest
- Distributed Storage Class MemoryTM at Scale
- Patent-pending SW abstraction (virtualization) of storage-class memory (SCM)
- Distributes dataset on large-scale clusters (i.e., not just a single node or device)
- New Indexing technologies
- Built from the ground up and patent-pending
- Go well beyond LSM- and B- tree schemes (textbook methods) not designed for modern hardware
- HW-SW Parallelism
- Exploits full benefit of multi-core processors in distributed systems
- Optimizes bandwidth of shared resources (like storage) pushing limits to physical boundaries
- Just-in-Time-Compilation (JITC)
- Built-into distributed architecture
- Accomplishes query and aggregation offload/acceleration
- Flash Optimized
- Optimizes Flash properties making SSDs viable in real-time Big Data applications
- Architected to utilize all the SSD bandwidth
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Ease of Use
- In the cloud
- On containerized storage
In Any Environment
- Runs on commodity or custom hardware
- Optimized for any form of NVM SSDs - Flash, Storage Class Memories