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  1. Stackups
  2. Application & Data
  3. In-Memory Databases
  4. In Memory Databases
  5. Apache Ignite vs XAP

Apache Ignite vs XAP

OverviewComparisonAlternatives

Overview

Apache Ignite
Apache Ignite
Stacks110
Followers168
Votes41
GitHub Stars5.0K
Forks1.9K
XAP
XAP
Stacks1
Followers2
Votes0

Apache Ignite vs XAP: What are the differences?

Apache Ignite: *An open-source distributed database, caching and processing platform *. It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale; XAP: The In-Memory computing solution to scale your applications. It provides an essential set of data store features, such as transactions, indexes, and query language (SQL-like queries). It also handles common functions such as messaging, event processing, data access, and transaction processing (ACID compliant) completely and exclusively in-memory.

Apache Ignite and XAP can be primarily classified as "In-Memory Databases" tools.

Some of the features offered by Apache Ignite are:

  • Memory-Centric Storage
  • Distributed SQL
  • Distributed Key-Value

On the other hand, XAP provides the following key features:

  • In-memory data grid
  • Stream processing for mission-critical applications
  • Empowers event-driven microservices and distributed applications for real-time big data innovation

Apache Ignite is an open source tool with 2.95K GitHub stars and 1.41K GitHub forks. Here's a link to Apache Ignite's open source repository on GitHub.

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Detailed Comparison

Apache Ignite
Apache Ignite
XAP
XAP

It is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads delivering in-memory speeds at petabyte scale

It provides an essential set of data store features, such as transactions, indexes, and query language (SQL-like queries). It also handles common functions such as messaging, event processing, data access, and transaction processing (ACID compliant) completely and exclusively in-memory.

Memory-Centric Storage; Distributed SQL; Distributed Key-Value
In-memory data grid; Stream processing for mission-critical applications; Empowers event-driven microservices and distributed applications for real-time big data innovation
Statistics
GitHub Stars
5.0K
GitHub Stars
-
GitHub Forks
1.9K
GitHub Forks
-
Stacks
110
Stacks
1
Followers
168
Followers
2
Votes
41
Votes
0
Pros & Cons
Pros
  • 5
    Multiple client language support
  • 5
    Written in java. runs on jvm
  • 5
    Free
  • 5
    High Avaliability
  • 4
    Load balancing
No community feedback yet
Integrations
MongoDB
MongoDB
MySQL
MySQL
Apache Spark
Apache Spark
Spring
Spring
Java
Java
.NET
.NET

What are some alternatives to Apache Ignite, XAP?

Redis

Redis

Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.

Hazelcast

Hazelcast

With its various distributed data structures, distributed caching capabilities, elastic nature, memcache support, integration with Spring and Hibernate and more importantly with so many happy users, Hazelcast is feature-rich, enterprise-ready and developer-friendly in-memory data grid solution.

Aerospike

Aerospike

Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.

MemSQL

MemSQL

MemSQL converges transactions and analytics for sub-second data processing and reporting. Real-time businesses can build robust applications on a simple and scalable infrastructure that complements and extends existing data pipelines.

SAP HANA

SAP HANA

It is an application that uses in-memory database technology that allows the processing of massive amounts of real-time data in a short time. The in-memory computing engine allows it to process data stored in RAM as opposed to reading it from a disk.

VoltDB

VoltDB

VoltDB is a fundamental redesign of the RDBMS that provides unparalleled performance and scalability on bare-metal, virtualized and cloud infrastructures. VoltDB is a modern in-memory architecture that supports both SQL + Java with data durability and fault tolerance.

Tarantool

Tarantool

It is designed to give you the flexibility, scalability, and performance that you want, as well as the reliability and manageability that you need in mission-critical applications

Azure Redis Cache

Azure Redis Cache

It perfectly complements Azure database services such as Cosmos DB. It provides a cost-effective solution to scale read and write throughput of your data tier. Store and share database query results, session states, static contents, and more using a common cache-aside pattern.

KeyDB

KeyDB

KeyDB is a fully open source database that aims to make use of all hardware resources. KeyDB makes it possible to breach boundaries often dictated by price and complexity.

LokiJS

LokiJS

LokiJS is a document oriented database written in javascript, published under MIT License. Its purpose is to store javascript objects as documents in a nosql fashion and retrieve them with a similar mechanism. Runs in node (including cordova/phonegap and node-webkit), nativescript and the browser.

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