Why and when to use LeanXcale

 

Real-time analytics

Technology: Create services processing analytical queries on operational data with no delay: no ETL, no complex architectures, high performance. Take advantage of ultra-fast Key-Value interface for high rate insertions.

Benefit: Real-time analytics allows companies to react promptly, create new services and reduce management costs.

It's interesting for:
  • Real-time apps, where every second count, such as stock trading, fraud detection, ad-tech, travel tech, gaming, patient health monitoring or machine analysis.
  • Connected data apps, where integrated business data is critical, such as banking, insurance, retail, e-commerce or telco.
  • Event analytics on operational data: manufacturers can track machines every second to predict: IoT, green energy or inventory management.

Operational data lake

Technology: Have a platform equivalent to a data lake at price, but granting transactional consistency and with much faster response time: This means that you will get insights from a coherent picture, faster.

Benefit: Avoid your data scientist waiting for full loads to waste their time creating models, training it and having results over inconsistent views.

It's interesting for: Data lake users and companies that are in a continuous learning process about customers, business processes, and operations: banking, insurance, retail, telco, ad-tech, travel-tech, fast-growing companies, etc.

Massive scalability

Technology: Iguazu tech allows LeanXcale to scale horizontally over inexpensive hardware to hundreds of nodes, with an impressive performance per core, and always with a linear performance.

Benefit: No matter how your application grows, your database architecture will be prepared. Be ready to process up to millions of transactions per second, store up to petabytes or query up to billions of rows instantly.

It's interesting for: Verticals, which use still mainframe: Banking, Insurance, Telco, Healthcare, Government, Aviation and Retail.
 

Time-series database

Technology: LeanXcale automatically handles time-evolving data to keep the relevant timeframe in memory, deriving on faster response time. Additionally, LeanXcale can manage aggregation operations in parallel in the update queries with no conflicts at any scale.

Benefit: All these make ultimately LeanXcale the best option as data series database.

It's interesting for: Brokers, monitoring tools, inventory management tools, IoT, dev-ops or industrial telemetry.

Polyglot layer

Technology: LeanXcale is open to coordinate other database engines. View and join information among all databases portfolio. Query MongoDB, HBase, Neo4J and your RDBMS in their native API in a single view combining the data to create a single resultset.

Benefit: Develop fast and safer getting the most of each datastores you are using.

It's interesting for: All the companies that need to simplify their stacks and break the silos progressively.

Distributed and resilient database

Technology: LeanXcale data storage can move data fragments without disrupting the QoS of the transactions accessing them.

Benefit: This capacity allows transparent data replication, load balancing, elasticity, and resilience without any impact on performance and consistency.

It's interesting for: Follow-the-sun support, multinationals running operations in several continents or PaaS and SaaS platforms.
 

Versatile database

Technology: LeanXcale allows a single database that covers all the data management stack, from in-memory to big data queries.

Benefit: The more complex stack the much more complex to pivot or evolve.

It's interesting for: Startups and scale-ups that have a rapid evolution.

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