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ArangoDB vs RocksDB: What are the differences?

Introduction

ArangoDB and RocksDB are both popular databases used in various applications. However, they have key differences that set them apart from each other.

  1. Data Model: ArangoDB is a multi-model database that supports documents, graphs, and key-value pairs within a single database. On the other hand, RocksDB is a key-value store that is mainly used as an embedded database within other systems, providing high-performance storage for key-value pairs.

  2. Query Language: ArangoDB uses its query language called AQL (ArangoDB Query Language) which allows users to leverage the power of SQL-like queries for different data models. In contrast, RocksDB does not have a query language of its own, and the interaction with the database is usually done through a key-value API or other interfaces provided by the host system.

  3. Scalability: ArangoDB is designed to be a distributed database from the ground up, allowing for easy horizontal scaling across multiple servers. RocksDB, on the other hand, is mainly used as an embedded database within single servers or applications, limiting its scalability options compared to ArangoDB.

  4. Consistency and Durability: ArangoDB provides options for users to choose between different levels of consistency (from eventual consistency to strong consistency) and offers various durability options to suit different use cases. RocksDB focuses on providing high performance and durability through features like write-ahead logging, but the consistency model is often determined by the application using RocksDB.

  5. Community and Ecosystem: ArangoDB has a thriving community that actively contributes to the development of the database, and it also has a wide range of plugins and integrations available to extend its functionality. On the other hand, RocksDB, being primarily an embedded database, relies heavily on the ecosystem of the host system it is integrated with, which may vary in terms of support and plugins available.

  6. Use Cases: Due to its multi-model capabilities, ArangoDB is well-suited for applications that require handling diverse types of data and relationships between them, such as social networks or content management systems. RocksDB, with its focus on high-performance key-value storage, is commonly used in applications that require fast and efficient data access, such as caching systems or distributed storage engines.

In Summary, ArangoDB and RocksDB differ in terms of data model support, query language, scalability, consistency, community support, and use cases, making them suitable for different types of applications.

Advice on ArangoDB and RocksDB
Needs advice
on
HBaseHBaseMilvusMilvus
and
RocksDBRocksDB

I am researching different querying solutions to handle ~1 trillion records of data (in the realm of a petabyte). The data is mostly textual. I have identified a few options: Milvus, HBase, RocksDB, and Elasticsearch. I was wondering if there is a good way to compare the performance of these options (or if anyone has already done something like this). I want to be able to compare the speed of ingesting and querying textual data from these tools. Does anyone have information on this or know where I can find some? Thanks in advance!

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Recommends

You've probably come to a decision already but for those reading...here are some resources we put together to help people learn more about Milvus and other databases https://zilliz.com/comparison and https://github.com/zilliztech/VectorDBBench. I don't think they include RocksDB or HBase yet (you could could recommend on GitHub) but hopefully they help answer your Elastic Search questions.

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Needs advice
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ArangoDBArangoDB
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PostgreSQLPostgreSQL

Hello All, I'm building an app that will enable users to create documents using ckeditor or TinyMCE editor. The data is then stored in a database and retrieved to display to the user, these docs can contain image data also. The number of pages generated for a single document can go up to 1000. Therefore by design, each page is stored in a separate JSON. I'm wondering which database is the right one to choose between ArangoDB and PostgreSQL. Your thoughts, advice please. Thanks, Kashyap

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Recommends
on
MongoDBMongoDB

try mongodb first.

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Attila Fulop
Recommends

Which Graph DB features are you planning to use?

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Pros of ArangoDB
Pros of RocksDB
  • 37
    Grahps and documents in one DB
  • 26
    Intuitive and rich query language
  • 25
    Good documentation
  • 25
    Open source
  • 21
    Joins for collections
  • 15
    Foxx is great platform
  • 14
    Great out of the box web interface with API playground
  • 6
    Good driver support
  • 6
    Low maintenance efforts
  • 6
    Clustering
  • 5
    Easy microservice creation with foxx
  • 4
    You can write true backendless apps
  • 2
    Managed solution available
  • 0
    Performance
  • 5
    Very fast
  • 3
    Made by Facebook
  • 2
    Consistent performance
  • 1
    Ability to add logic to the database layer where needed

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Cons of ArangoDB
Cons of RocksDB
  • 3
    Web ui has still room for improvement
  • 2
    No support for blueprints standard, using custom AQL
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    What is ArangoDB?

    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.

    What is RocksDB?

    RocksDB is an embeddable persistent key-value store for fast storage. RocksDB can also be the foundation for a client-server database but our current focus is on embedded workloads. RocksDB builds on LevelDB to be scalable to run on servers with many CPU cores, to efficiently use fast storage, to support IO-bound, in-memory and write-once workloads, and to be flexible to allow for innovation.

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    What companies use ArangoDB?
    What companies use RocksDB?
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    What tools integrate with ArangoDB?
    What tools integrate with RocksDB?

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    Blog Posts

    Jan 26 2022 at 4:34AM

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    What are some alternatives to ArangoDB and RocksDB?
    Neo4j
    Neo4j stores data in nodes connected by directed, typed relationships with properties on both, also known as a Property Graph. It is a high performance graph store with all the features expected of a mature and robust database, like a friendly query language and ACID transactions.
    MongoDB
    MongoDB stores data in JSON-like documents that can vary in structure, offering a dynamic, flexible schema. MongoDB was also designed for high availability and scalability, with built-in replication and auto-sharding.
    PostgreSQL
    PostgreSQL is an advanced object-relational database management system that supports an extended subset of the SQL standard, including transactions, foreign keys, subqueries, triggers, user-defined types and functions.
    Cassandra
    Partitioning means that Cassandra can distribute your data across multiple machines in an application-transparent matter. Cassandra will automatically repartition as machines are added and removed from the cluster. Row store means that like relational databases, Cassandra organizes data by rows and columns. The Cassandra Query Language (CQL) is a close relative of SQL.
    OrientDB
    It is an open source NoSQL database management system written in Java. It is a Multi-model database, supporting graph, document, key/value, and object models, but the relationships are managed as in graph databases with direct connections between records.
    See all alternatives