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HBase vs Kyoto Tycoon: What are the differences?
HBase: The Hadoop database, a distributed, scalable, big data store. Apache HBase is an open-source, distributed, versioned, column-oriented store modeled after Google' Bigtable: A Distributed Storage System for Structured Data by Chang et al. Just as Bigtable leverages the distributed data storage provided by the Google File System, HBase provides Bigtable-like capabilities on top of Apache Hadoop; 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.
HBase and Kyoto Tycoon can be primarily classified as "Databases" tools.
HBase is an open source tool with 2.91K GitHub stars and 2.01K GitHub forks. Here's a link to HBase's open source repository on GitHub.
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!
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.
Pros of HBase
- Performance9
- OLTP5
- Fast Point Queries1
Pros of Kyoto Tycoon
- RESTful API2
- Simple, persistent Key-Value Store2
- Easy setup1
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