RocksDB vs ToroDB

Overview

ToroDB

Stacks0

Followers7

Votes0

GitHub Stars12

Forks2

RocksDB

Stacks141

Followers290

Votes11

GitHub Stars30.9K

Forks6.6K

RocksDB vs ToroDB: What are the differences?

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; ToroDB: Open source, document-oriented, JSON database that runs on top of PostgreSQL. ToroDB is an open source, document-oriented, JSON database that runs on top of PostgreSQL, providing storage and I/O savings and ACID semantics. ToroDB is MongoDB-compatible, so you can use Mongo clients to connect to it.

RocksDB and ToroDB belong to "Databases" category of the tech stack.

Some of the features offered by RocksDB are:

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

On the other hand, ToroDB provides the following key features:

Document-oriented (JSON)
Store data reliabily and durably with PostgreSQL
Use MongoDB clients to connect to it

RocksDB and ToroDB are both open source tools. RocksDB with 14.3K GitHub stars and 3.12K forks on GitHub appears to be more popular than ToroDB with 10 GitHub stars and 2 GitHub forks.

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Advice on ToroDB, RocksDB

Feb 9, 2022

Needs adviceon

Milvus

HBase

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!

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Comments

Detailed Comparison

ToroDB	RocksDB
ToroDB is an open source, document-oriented, JSON database that runs on top of PostgreSQL, providing storage and I/O savings and ACID semantics. ToroDB is MongoDB-compatible, so you can use Mongo clients to connect to it.	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.
Document-oriented (JSON); Store data reliabily and durably with PostgreSQL; Use MongoDB clients to connect to it; High concurrency and I/O and storage savings; ACID semantics: atomic batch insertions; ACID semantics: queries run fully isolated;Open source, AGPLv3 licensed	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 12	GitHub Stars 30.9K
GitHub Forks 2	GitHub Forks 6.6K
Stacks 0	Stacks 141
Followers 7	Followers 290
Votes 0	Votes 11
Pros & Cons
No community feedback yet	Pros 5 Very fast 3 Made by Facebook 2 Consistent performance 1 Ability to add logic to the database layer where needed
Integrations
PostgreSQL	No integrations available

What are some alternatives to ToroDB, RocksDB?

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

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

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

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 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

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 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

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.

Related Comparisons

Some of the features offered by RocksDB are:

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

On the other hand, ToroDB provides the following key features:

Document-oriented (JSON)
Store data reliabily and durably with PostgreSQL
Use MongoDB clients to connect to it

RocksDB and ToroDB are both open source tools. RocksDB with 14.3K GitHub stars and 3.12K forks on GitHub appears to be more popular than ToroDB with 10 GitHub stars and 2 GitHub forks.

RocksDB vs ToroDB