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Riak vs RocksDB: What are the differences?
- Data Model: Riak is a distributed key-value store, whereas RocksDB is a persistent key-value store that runs on a single node.
- Consistency: Riak offers high availability and eventual consistency, while RocksDB ensures strong consistency as it operates on a single node.
- Scale-out: Riak can easily scale out by adding more nodes to the cluster, while RocksDB is more suited for applications that do not require distributed storage.
- Fault Tolerance: Riak is designed to handle failures and maintain data availability across the cluster, while RocksDB relies on the fault tolerance mechanisms of the underlying file system.
- Replication: Riak supports multi-datacenter replication for widespread data distribution, whereas RocksDB does not have built-in support for multi-datacenter replication.
- Performance: RocksDB typically offers higher performance for read and write operations compared to Riak due to its single-node architecture and optimized data storage strategies.
In Summary, Riak and RocksDB differ in their data models, consistency levels, scalability, fault tolerance, replication capabilities, and performance characteristics.
Advice on Riak and RocksDB
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!
Replies (1)
Emily Kurze
at Zilliz · | 2 upvotes · 3.2K views
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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Learn MorePros of Riak
Pros of RocksDB
Pros of Riak
- High Performance14
- High Availability11
- Easy Scalability9
- Flexible5
- Strong Consistency1
- Eventual Consistency1
- Distributed1
- Multi datacenter deployments1
- Reliable1
Pros of RocksDB
- Very fast5
- Made by Facebook3
- Consistent performance2
- Ability to add logic to the database layer where needed1
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What is Riak?
Riak is a distributed database designed to deliver maximum data availability by distributing data across multiple servers. As long as your client can reach one Riak server, it should be able to write data. In most failure scenarios, the data you want to read should be available, although it may not be the most up-to-date version of that data.
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 Riak?
What companies use RocksDB?
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What tools integrate with Riak?
What tools integrate with RocksDB?
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What are some alternatives to Riak and RocksDB?
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.
Aerospike
Aerospike is an open-source, modern database built from the ground up to push the limits of flash storage, processors and networks. It was designed to operate with predictable low latency at high throughput with uncompromising reliability – both high availability and ACID guarantees.
Couchbase
Developed as an alternative to traditionally inflexible SQL databases, the Couchbase NoSQL database is built on an open source foundation and architected to help developers solve real-world problems and meet high scalability demands.
Redis
Redis is an open source (BSD licensed), in-memory data structure store, used as a database, cache, and message broker. Redis provides data structures such as strings, hashes, lists, sets, sorted sets with range queries, bitmaps, hyperloglogs, geospatial indexes, and streams.
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.