Ignite alternatives and similar packages
Based on the "Database" category.
Alternatively, view Apache Ignite alternatives based on common mentions on social networks and blogs.
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Event Store
The open-source, functional database with Complex Event Processing in JavaScript. https://geteventstore.com -
SqlKata Query Builder
SQL query builder, written in c#, helps you build complex queries easily, supports SqlServer, MySql and PostgreSql -
NReco LambdaParser
Runtime parser for string expressions (formulas, method calls). Builds dynamic LINQ expression tree and compiles it to lambda delegate. -
StringDB
StringDB is a modular, key/value pair archival DB designed to consume tiny amounts of ram & produce tiny databases. -
Mailcloud.Hydra
A set of components to take the most advantage of performance and capacity of Azure Storage.
Pixel-Perfect Multi-Platform Applications with C# and XAML
* Code Quality Rankings and insights are calculated and provided by Lumnify.
They vary from L1 to L5 with "L5" being the highest. Visit our partner's website for more details.
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README
Apache Ignite
What is Apache Ignite?
Apache Ignite is a horizontally scalable, fault-tolerant distributed in-memory computing platform for building real-time applications that can process terabytes of data with in-memory speed.
Multi-Tier Storage
Apache Ignite is designed to work with memory, disk, and Intel Optane as active storage tiers. The memory tier allows using DRAM and Intel® Optane™ operating in the Memory Mode for data storage and processing needs. The disk tier is optional with the support of two options -- you can persist data in an external database or keep it in the Ignite native persistence. SSD, Flash, HDD, or Intel Optane operating in the AppDirect Mode can be used as a storage device.
Ignite Native Persistence
Even though Apache Ignite is broadly used as a caching layer on top of external databases, it comes with its native persistence - a distributed, ACID, and SQL-compliant disk-based store. The native persistence integrates into the Ignite multi-tier storage as a disk tier that can be turned on to let Ignite store more data on disk than it can cache in memory and to enable fast cluster restarts.
ACID Compliance
Data stored in Ignite is ACID-compliant both in memory and on disk, making Ignite a strongly consistent system. Ignite transactions work across the network and can span multiple servers.
ANSI SQL Support
Apache Ignite comes with a ANSI-99 compliant, horizontally scalable, and fault-tolerant SQL engine that allows you to interact with Ignite as with a regular SQL database using JDBC, ODBC drivers, or native SQL APIs available for Java, C#, C++, Python, and other programming languages. Ignite supports all DML commands, including SELECT, UPDATE, INSERT, and DELETE queries as well as a subset of DDL commands relevant for distributed systems.
Machine Learning and High-Performance Computing
Apache Ignite Machine Learning is a set of simple, scalable, and efficient tools that allow building predictive machine learning models without costly data transfers. The rationale for adding machine and deep learning to Apache Ignite is quite simple. Today's data scientists have to deal with two major factors that keep ML from mainstream adoption.
High-performance computing (HPC) is the ability to process data and perform complex calculations at high speeds. Using Apache Ignite as a high-performance compute cluster, you can turn a group of commodity machines or a cloud environment into a distributed supercomputer of interconnected Ignite nodes. Ignite enables speed and scale by processing records in memory and reducing network utilization with APIs for data and compute-intensive calculations. Those APIs implement the MapReduce paradigm and allow you to run arbitrary tasks across the cluster of nodes.
*Note that all licence references and agreements mentioned in the Ignite README section above
are relevant to that project's source code only.