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IBM DB2 vs RocksDB: What are the differences?
IBM DB2: A family of database server products developed by IBM. DB2 for Linux, UNIX, and Windows is optimized to deliver industry-leading performance across multiple workloads, while lowering administration, storage, development, and server costs; 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.
IBM DB2 and RocksDB can be primarily classified as "Databases" tools.
"Rock solid and very scalable" is the primary reason why developers consider IBM DB2 over the competitors, whereas "Very fast" was stated as the key factor in picking RocksDB.
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.
According to the StackShare community, IBM DB2 has a broader approval, being mentioned in 7 company stacks & 9 developers stacks; compared to RocksDB, which is listed in 6 company stacks and 7 developer stacks.
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 IBM DB2
- Rock solid and very scalable7
- BLU Analytics is amazingly fast5
- Native XML support2
- Secure by default2
- Easy2
- Best performance1
Pros of RocksDB
- Very fast5
- Made by Facebook3
- Consistent performance2
- Ability to add logic to the database layer where needed1
