Software Alternatives, Accelerators & Startups

ArangoDB VS Apache Flink

Compare ArangoDB VS Apache Flink and see what are their differences

Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

ArangoDB logo ArangoDB

A distributed open-source database with a flexible data model for documents, graphs, and key-values.

Apache Flink logo Apache Flink

Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.
  • ArangoDB Landing page
    Landing page //
    2023-01-20
  • Apache Flink Landing page
    Landing page //
    2023-10-03

ArangoDB features and specs

  • Graph DB

Apache Flink features and specs

  • Real-time Stream Processing
    Apache Flink is designed for real-time data streaming, offering low-latency processing capabilities that are essential for applications requiring immediate data insights.
  • Event Time Processing
    Flink supports event time processing, which allows it to handle out-of-order events effectively and provide accurate results based on the time events actually occurred rather than when they were processed.
  • State Management
    Flink provides robust state management features, making it easier to maintain and query state across distributed nodes, which is crucial for managing long-running applications.
  • Fault Tolerance
    The framework includes built-in mechanisms for fault tolerance, such as consistent checkpoints and savepoints, ensuring high reliability and data consistency even in the case of failures.
  • Scalability
    Apache Flink is highly scalable, capable of handling both batch and stream processing workloads across a distributed cluster, making it suitable for large-scale data processing tasks.
  • Rich Ecosystem
    Flink has a rich set of APIs and integrations with other big data tools, such as Apache Kafka, Apache Hadoop, and Apache Cassandra, enhancing its versatility and ease of integration into existing data pipelines.

Possible disadvantages of Apache Flink

  • Complexity
    Flink’s advanced features and capabilities come with a steep learning curve, making it more challenging to set up and use compared to simpler stream processing frameworks.
  • Resource Intensive
    The framework can be resource-intensive, requiring substantial memory and CPU resources for optimal performance, which might be a concern for smaller setups or cost-sensitive environments.
  • Community Support
    While growing, the community around Apache Flink is not as large or mature as some other big data frameworks like Apache Spark, potentially limiting the availability of community-contributed resources and support.
  • Ecosystem Maturity
    Despite its integrations, the Flink ecosystem is still maturing, and certain tools and plugins may not be as developed or stable as those available for more established frameworks.
  • Operational Overhead
    Running and maintaining a Flink cluster can involve significant operational overhead, including monitoring, scaling, and troubleshooting, which might require a dedicated team or additional expertise.

ArangoDB videos

ArangoDB and Foxx Framework, deeper dive. WHILT#17

Apache Flink videos

GOTO 2019 • Introduction to Stateful Stream Processing with Apache Flink • Robert Metzger

More videos:

  • Tutorial - Apache Flink Tutorial | Flink vs Spark | Real Time Analytics Using Flink | Apache Flink Training
  • Tutorial - How to build a modern stream processor: The science behind Apache Flink - Stefan Richter

Category Popularity

0-100% (relative to ArangoDB and Apache Flink)
Databases
82 82%
18% 18
Big Data
0 0%
100% 100
NoSQL Databases
100 100%
0% 0
Stream Processing
0 0%
100% 100

User comments

Share your experience with using ArangoDB and Apache Flink. For example, how are they different and which one is better?
Log in or Post with

Reviews

These are some of the external sources and on-site user reviews we've used to compare ArangoDB and Apache Flink

ArangoDB Reviews

9 Best MongoDB alternatives in 2019
ArangoDB is a native multi-model DBMS system. It supports three data models with one database core and a unified query language AQL. Its query language is declarative which helps you to compare different data access patterns by using a single query.
Source: www.guru99.com
Top 15 Free Graph Databases
ArangoDB is a distributed free and open-source database with a flexible data model for documents, graphs, and key-values. Build high performance applications using a convenient SQL-like query language or JavaScript extensions. ArangoDB
ArangoDB vs Neo4j - What you can't do with Neo4j
Scalability needs and ArangoDB ArangoDB is cluster ready for graphs, documents and key/values. ArangoDB is suitable for e.g. recommendation engines, personalization, Knowledge Graphs or other graph-related use cases. ArangoDB provides special features for scale-up (Vertex-centric indices) and scale-out (SmartGraphs).

Apache Flink Reviews

We have no reviews of Apache Flink yet.
Be the first one to post

Social recommendations and mentions

Based on our record, Apache Flink should be more popular than ArangoDB. It has been mentiond 41 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

ArangoDB mentions (6)

View more

Apache Flink mentions (41)

  • What is Apache Flink? Exploring Its Open Source Business Model, Funding, and Community
    Continuous Learning: Leverage online tutorials from the official Flink website and attend webinars for deeper insights. - Source: dev.to / 1 day ago
  • Is RisingWave the Next Apache Flink?
    Apache Flink, known initially as Stratosphere, is a distributed stream processing engine initiated by a group of researchers at TU Berlin. Since its initial release in May 2011, Flink has gained immense popularity in both academia and industry. And it is currently the most well-known streaming system globally (challenge me if you think I got it wrong!). - Source: dev.to / 14 days ago
  • Every Database Will Support Iceberg — Here's Why
    Apache Iceberg defines a table format that separates how data is stored from how data is queried. Any engine that implements the Iceberg integration — Spark, Flink, Trino, DuckDB, Snowflake, RisingWave — can read and/or write Iceberg data directly. - Source: dev.to / 19 days ago
  • RisingWave Turns Four: Our Journey Beyond Democratizing Stream Processing
    The last decade saw the rise of open-source frameworks like Apache Flink, Spark Streaming, and Apache Samza. These offered more flexibility but still demanded significant engineering muscle to run effectively at scale. Companies using them often needed specialized stream processing engineers just to manage internal state, tune performance, and handle the day-to-day operational challenges. The barrier to entry... - Source: dev.to / 24 days ago
  • Twitter's 600-Tweet Daily Limit Crisis: Soaring GCP Costs and the Open Source Fix Elon Musk Ignored
    Apache Flink: Flink is a unified streaming and batching platform developed under the Apache Foundation. It provides support for Java API and a SQL interface. Flink boasts a large ecosystem and can seamlessly integrate with various services, including Kafka, Pulsar, HDFS, Iceberg, Hudi, and other systems. - Source: dev.to / about 1 month ago
View more

What are some alternatives?

When comparing ArangoDB and Apache Flink, you can also consider the following products

Redis - Redis is an open source in-memory data structure project implementing a distributed, in-memory key-value database with optional durability.

Apache Spark - Apache Spark is an engine for big data processing, with built-in modules for streaming, SQL, machine learning and graph processing.

MongoDB - MongoDB (from "humongous") is a scalable, high-performance NoSQL database.

Amazon Kinesis - Amazon Kinesis services make it easy to work with real-time streaming data in the AWS cloud.

OrientDB - OrientDB - The World's First Distributed Multi-Model NoSQL Database with a Graph Database Engine.

Spring Framework - The Spring Framework provides a comprehensive programming and configuration model for modern Java-based enterprise applications - on any kind of deployment platform.