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  5. Kyoto Tycoon vs RocksDB

Kyoto Tycoon vs RocksDB

OverviewDecisionsComparisonAlternatives

Overview

Kyoto Tycoon
Kyoto Tycoon
Stacks3
Followers17
Votes5
RocksDB
RocksDB
Stacks141
Followers290
Votes11
GitHub Stars30.9K
Forks6.6K

Kyoto Tycoon vs RocksDB: What are the differences?

Kyoto Tycoon: A handy cache/storage server. Kyoto Tycoon is a lightweight database server with auto expiration mechanism, which is useful to handle cache data and persistent data of various applications. Kyoto Tycoon is also a package of network interface to the DBM called Kyoto Cabinet; RocksDB: Embeddable persistent key-value store for fast storage, developed and maintained by Facebook Database Engineering Team. 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.

Kyoto Tycoon and RocksDB can be categorized as "Databases" tools.

RocksDB is an open source tool with 14.3K GitHub stars and 3.12K GitHub forks. Here's a link to RocksDB's open source repository on GitHub.

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Advice on Kyoto Tycoon, RocksDB

D
D

Feb 9, 2022

Needs adviceonMilvusMilvusHBaseHBaseRocksDBRocksDB

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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Comments

Detailed Comparison

Kyoto Tycoon
Kyoto Tycoon
RocksDB
RocksDB

Kyoto Tycoon is a lightweight database server with auto expiration mechanism, which is useful to handle cache data and persistent data of various applications. Kyoto Tycoon is also a package of network interface to the DBM called Kyoto Cabinet.

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.

-
Designed for application servers wanting to store up to a few terabytes of data on locally attached Flash drives or in RAM;Optimized for storing small to medium size key-values on fast storage -- flash devices or in-memory;Scales linearly with number of CPUs so that it works well on ARM processors
Statistics
GitHub Stars
-
GitHub Stars
30.9K
GitHub Forks
-
GitHub Forks
6.6K
Stacks
3
Stacks
141
Followers
17
Followers
290
Votes
5
Votes
11
Pros & Cons
Pros
  • 2
    Simple, persistent Key-Value Store
  • 2
    RESTful API
  • 1
    Easy setup
Pros
  • 5
    Very fast
  • 3
    Made by Facebook
  • 2
    Consistent performance
  • 1
    Ability to add logic to the database layer where needed

What are some alternatives to Kyoto Tycoon, RocksDB?

MongoDB

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.

MySQL

MySQL

The MySQL software delivers a very fast, multi-threaded, multi-user, and robust SQL (Structured Query Language) database server. MySQL Server is intended for mission-critical, heavy-load production systems as well as for embedding into mass-deployed software.

PostgreSQL

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.

Microsoft SQL Server

Microsoft SQL Server

Microsoft® SQL Server is a database management and analysis system for e-commerce, line-of-business, and data warehousing solutions.

SQLite

SQLite

SQLite is an embedded SQL database engine. Unlike most other SQL databases, SQLite does not have a separate server process. SQLite reads and writes directly to ordinary disk files. A complete SQL database with multiple tables, indices, triggers, and views, is contained in a single disk file.

Cassandra

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.

Memcached

Memcached

Memcached is an in-memory key-value store for small chunks of arbitrary data (strings, objects) from results of database calls, API calls, or page rendering.

MariaDB

MariaDB

Started by core members of the original MySQL team, MariaDB actively works with outside developers to deliver the most featureful, stable, and sanely licensed open SQL server in the industry. MariaDB is designed as a drop-in replacement of MySQL(R) with more features, new storage engines, fewer bugs, and better performance.

RethinkDB

RethinkDB

RethinkDB is built to store JSON documents, and scale to multiple machines with very little effort. It has a pleasant query language that supports really useful queries like table joins and group by, and is easy to setup and learn.

ArangoDB

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.

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