Apache Flink vs Orchestrate

Overview

Orchestrate

Stacks5

Followers16

Votes0

Apache Flink

Stacks535

Followers879

Votes38

GitHub Stars25.4K

Forks13.7K

Apache Flink vs Orchestrate: What are the differences?

Developers describe Apache Flink as "Fast and reliable large-scale data processing engine". 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. On the other hand, Orchestrate is detailed as "Database as a Service. Add Search, Time-Ordered Events, Geospatial or Graph Queries Fast with a REST API". Orchestrate is a managed database service that delivers a single access point to full-text search, time-ordered events, geospatial and graph queries through a REST API. It allows developers to build complete apps or add features to existing ones fast, without the operational burden of deploying and managing multiple databases themselves.

Apache Flink belongs to "Big Data Tools" category of the tech stack, while Orchestrate can be primarily classified under "NoSQL Database as a Service".

Some of the features offered by Apache Flink are:

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

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

Search
Geospatial
Time-series Events

Apache Flink is an open source tool with 9.11K GitHub stars and 4.86K GitHub forks. Here's a link to Apache Flink's open source repository on GitHub.

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Advice on Orchestrate, Apache Flink

Nilesh

Technical Architect at Self Employed

Jul 8, 2020

Needs adviceon

Elasticsearch

Kafka

We have a Kafka topic having events of type A and type B. We need to perform an inner join on both type of events using some common field (primary-key). The joined events to be inserted in Elasticsearch.

In usual cases, type A and type B events (with same key) observed to be close upto 15 minutes. But in some cases they may be far from each other, lets say 6 hours. Sometimes event of either of the types never come.

In all cases, we should be able to find joined events instantly after they are joined and not-joined events within 15 minutes.

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Comments

Detailed Comparison

Orchestrate	Apache Flink
Orchestrate is a managed database service that delivers a single access point to full-text search, time-ordered events, geospatial and graph queries through a REST API. It allows developers to build complete apps or add features to existing ones fast, without the operational burden of deploying and managing multiple databases themselves.	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.
Search; Geospatial; Time-series Events; Graph; JSON Object Store; 3x Data Replication; Daily Backups; 24 x 365 Support; HTTP/REST Based API;	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 5	Stacks 535
Followers 16	Followers 879
Votes 0	Votes 38
Pros & Cons
No community feedback yet	Pros 16 Unified batch and stream processing 8 Out-of-the box connector to kinesis,s3,hdfs 8 Easy to use streaming apis 4 Open Source 2 Low latency
Integrations
No integrations available	YARN Hadoop Hadoop HBase Kafka

What are some alternatives to Orchestrate, Apache Flink?

Amazon DynamoDB

With it , you can offload the administrative burden of operating and scaling a highly available distributed database cluster, while paying a low price for only what you use.

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.

Azure Cosmos DB

Azure DocumentDB is a fully managed NoSQL database service built for fast and predictable performance, high availability, elastic scaling, global distribution, and ease of development.

Cloud Firestore

Cloud Firestore is a NoSQL document database that lets you easily store, sync, and query data for your mobile and web apps - at global scale.

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.

Cloudant

Cloudant’s distributed database as a service (DBaaS) allows developers of fast-growing web and mobile apps to focus on building and improving their products, instead of worrying about scaling and managing databases on their own.

Google Cloud Bigtable

Google Cloud Bigtable offers you a fast, fully managed, massively scalable NoSQL database service that's ideal for web, mobile, and Internet of Things applications requiring terabytes to petabytes of data. Unlike comparable market offerings, Cloud Bigtable doesn't require you to sacrifice speed, scale, or cost efficiency when your applications grow. Cloud Bigtable has been battle-tested at Google for more than 10 years—it's the database driving major applications such as Google Analytics and Gmail.

Related Comparisons

Some of the features offered by Apache Flink are:

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

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

Search
Geospatial
Time-series Events

Apache Flink is an open source tool with 9.11K GitHub stars and 4.86K GitHub forks. Here's a link to Apache Flink's open source repository on GitHub.

Apache Flink vs Orchestrate