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CrateIO vs HBase: What are the differences?
CrateIO: The Distributed Database for Docker. Crate is a distributed data store. Simply install Crate directly on your application servers and make the big centralized database a thing of the past. Crate takes care of synchronization, sharding, scaling, and replication even for mammoth data sets; 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.
CrateIO and HBase can be primarily classified as "Databases" tools.
"Simplicity" is the primary reason why developers consider CrateIO over the competitors, whereas "Performance" was stated as the key factor in picking HBase.
CrateIO and HBase are both open source tools. HBase with 2.91K GitHub stars and 2.01K forks on GitHub appears to be more popular than CrateIO with 2.49K GitHub stars and 333 GitHub forks.
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 CrateIO
- Simplicity3
- Scale2
- Open source2
Pros of HBase
- Performance9
- OLTP5
- Fast Point Queries1
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