Apache Flink vs Realm
Overview
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Detailed Comparison
The Realm Mobile Platform is a next-generation data layer for applications. Realm is reactive, concurrent, and lightweight, allowing you to work with live, native objects. | Apache Flink is an open source system for fast and versatile data analytics in clusters. Flink supports batch and streaming analytics, in one system. Analytical programs can be written in concise and elegant APIs in Java and Scala. |
Feels like Home - Realm’s data structures look like the Objects and Arrays of your language, but provide additional features such as: querying, relationships & graphs, thread safety, and more.;Memory-Efficient - Realm is not built on SQLite. Instead, a custom C++ core is used to provide memory-efficient access to your data by using Realm objects, which usually consume less RAM than native objects.;F-F-Fast! - Realm offers extraordinary performance compared to SQLite and other persistence solutions. | Hybrid batch/streaming runtime that supports batch processing and data streaming programs.;Custom memory management to guarantee efficient, adaptive, and highly robust switching between in-memory and data processing out-of-core algorithms.;Flexible and expressive windowing semantics for data stream programs;Built-in program optimizer that chooses the proper runtime operations for each program;Custom type analysis and serialization stack for high performance |
Statistics | |
GitHub Stars - | GitHub Stars 25.4K |
GitHub Forks - | GitHub Forks 13.7K |
Stacks 279 | Stacks 534 |
Followers 441 | Followers 879 |
Votes 16 | Votes 38 |
Pros & Cons | |
Pros
Cons
| Pros
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Integrations | |
| No integrations available | |
What are some alternatives to Realm, Apache Flink?
Apache Spark
Spark is a fast and general processing engine compatible with Hadoop data. It can run in Hadoop clusters through YARN or Spark's standalone mode, and it can process data in HDFS, HBase, Cassandra, Hive, and any Hadoop InputFormat. It is designed to perform both batch processing (similar to MapReduce) and new workloads like streaming, interactive queries, and machine learning.
Presto
Distributed SQL Query Engine for Big Data
Amazon Athena
Amazon Athena is an interactive query service that makes it easy to analyze data in Amazon S3 using standard SQL. Athena is serverless, so there is no infrastructure to manage, and you pay only for the queries that you run.
lakeFS
It is an open-source data version control system for data lakes. It provides a “Git for data” platform enabling you to implement best practices from software engineering on your data lake, including branching and merging, CI/CD, and production-like dev/test environments.
Druid
Druid is a distributed, column-oriented, real-time analytics data store that is commonly used to power exploratory dashboards in multi-tenant environments. Druid excels as a data warehousing solution for fast aggregate queries on petabyte sized data sets. Druid supports a variety of flexible filters, exact calculations, approximate algorithms, and other useful calculations.
Apache Kylin
Apache Kylin™ is an open source Distributed Analytics Engine designed to provide SQL interface and multi-dimensional analysis (OLAP) on Hadoop/Spark supporting extremely large datasets, originally contributed from eBay Inc.
Splunk
It provides the leading platform for Operational Intelligence. Customers use it to search, monitor, analyze and visualize machine data.
Apache Impala
Impala is a modern, open source, MPP SQL query engine for Apache Hadoop. Impala is shipped by Cloudera, MapR, and Amazon. With Impala, you can query data, whether stored in HDFS or Apache HBase – including SELECT, JOIN, and aggregate functions – in real time.
Vertica
It provides a best-in-class, unified analytics platform that will forever be independent from underlying infrastructure.
Azure Synapse
It is an analytics service that brings together enterprise data warehousing and Big Data analytics. It gives you the freedom to query data on your terms, using either serverless on-demand or provisioned resources—at scale. It brings these two worlds together with a unified experience to ingest, prepare, manage, and serve data for immediate BI and machine learning needs.
