Datahike VS OrbitDB

Datahike

A durable datalog database adaptable for distribution.

OrbitDB

OrbitDB is a serverless, distributed, peer-to-peer database.

Landing page //
2023-08-22

Landing page //
2023-09-26

Datahike features and specs

Persistence
Datahike is a persistent database, which means that it retains data across sessions and can be relied upon for storage that survives application restarts.
Datalog queries
Datahike supports Datalog queries, a powerful and expressive query language that is similar to Prolog, allowing for complex querying of data relationships.
Schema flexibility
Datahike provides schema flexibility that allows developers to define and evolve their data models without needing to perform migrations. This can significantly speed up development.
Immutable data structures
By utilizing immutable data structures, Datahike allows safe concurrent reads and writes, reducing the risk of data corruption and improving application stability.
Transactional support
Datahike offers ACID-compliant transactions, ensuring data integrity and consistent state even in the face of concurrent operations.
Integration with Datomic API
Datahike is designed to be compatible with the Datomic API, making it easier for developers familiar with Datomic to transition and leverage their knowledge.
Off-the-shelf scalability
The architecture of Datahike is conducive to scaling horizontally, providing flexibility to handle growing amounts of data and user load.

Possible disadvantages of Datahike

Relatively new ecosystem
Being a lesser-known and newer alternative compared to databases like Datomic, Datahike may have a smaller community and fewer resources like documentation and third-party integrations.
Performance limitations
While Datahike is designed to be lightweight and flexible, it may not match the performance of more mature databases, especially in very high-load or high-volume scenarios.
Limited features
Datahike may lack some advanced features present in other databases, such as sophisticated indexing or native support for certain types of analytics, which could be necessary for specific applications.
Java Virtual Machine (JVM) requirement
As it runs on the JVM, Datahike requires a Java runtime environment, which might not be ideal or convenient for projects seeking to minimize dependencies or employ lightweight deployment strategies.

OrbitDB features and specs

Decentralization
OrbitDB is a peer-to-peer database system built on top of IPFS, meaning it does not rely on a central server. This enhances data availability and resilience against censorship.
Offline-first Operation
Since OrbitDB is built on IPFS, it can operate without a constant connection to the internet, allowing data access and changes even when offline.
Versioning and Immutability
It provides built-in support for versioning and immutability of data, ensuring that historical records can be maintained and easily accessed.
Eventual Consistency
OrbitDB uses eventual consistency, which means all nodes will eventually reach the same data state. This is suitable for applications tolerant to eventual consistency rather than immediate data consistency.
Community and Open Source
As an open-source project, OrbitDB benefits from community contributions and transparency, allowing for improved security, auditing, and flexibility in modifications.

Possible disadvantages of OrbitDB

Complex Synchronization
Handling data consistency and synchronization in a decentralized manner can be complex, which may result in increased development and maintenance efforts.
Performance Overhead
Running on a peer-to-peer network can introduce performance overhead due to factors like data propagation delays and potential network instability.
Limited Ecosystem Support
Compared to more established databases, OrbitDB has a more limited ecosystem of tools and integrations, potentially requiring more custom development work.
Learning Curve
Developers may face a steeper learning curve due to the decentralized nature and unique characteristics of OrbitDB and IPFS.
Eventual Consistency Trade-offs
While eventual consistency can be a pro, it also means that applications requiring strict immediate consistency could face challenges when using OrbitDB.

Datahike videos

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OrbitDB videos

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On Telemetry for InterPlanetary Systems (OrbitDB + IPFS)

Category Popularity

0-100% (relative to Datahike and OrbitDB)

OrbitDB

Databases

53 53%

Databases

47% 47

Relational Databases

56 56%

Relational Databases

44% 44

Network & Admin

55 55%

Network & Admin

45% 45

NoSQL Databases

52 52%

NoSQL Databases

48% 48

User comments

Share your experience with using Datahike and OrbitDB. For example, how are they different and which one is better?

Social recommendations and mentions

Based on our record, OrbitDB should be more popular than Datahike. It has been mentiond 7 times since March 2021. We are tracking product recommendations and mentions on various public social media platforms and blogs. They can help you identify which product is more popular and what people think of it.

Datahike mentions (4)

The Ten Rules of Schema Growth
Datahike [0] provides similar functionality to datomic and is open source. It lacks some features however that Datomic does have [1]. [0]: https://github.com/replikativ/datahike. - Source: Hacker News / over 1 year ago
Is Datomic right for my use case?
You can also consider other durable Datalog options like datahike or datalevin which can work either as lib (SQLite style) or in a client-server setup; if you want to play with bi-temporality XTDB is a rock solid option with very good support and documentation. Source: almost 2 years ago
Max Datom: Interactive Datomic Tutorial
Oh really interesting. I didn't know about that. I was actually going threw the old Mendat code base and was considering using that. I would really like a pure Rust version of Datomic for embed use cases. There is all also Datahike, that is going in that direction too. It is maintained and actively developed. https://github.com/replikativ/datahike. - Source: Hacker News / about 3 years ago
Show HN: Matrix-CRDT – real-time collaborative apps using Matrix as backend
Having an Datomic like store backed by something like this. https://github.com/replikativ/datahike Is an Open Source variant of Datomic. Lambdaforge wants to eventually have this work with CRDTs. Using the Matrix ecosystem for this is quite interesting as it solves many problems for you already. - Source: Hacker News / over 3 years ago

OrbitDB mentions (7)

Show HN: TeaTime – static distributed library powered by SQLite, IPFS and GitHub
> (I'm looking into using Helia so that users are also contributing nodes in the network) I had to look that term up I was reminded of https://github.com/orbitdb/orbitdb#readme which seems like it may be much less rolling your own parts. - Source: Hacker News / 5 months ago
How to make a crowdsourced distributed metadata database?
Both use OrbitDB: Peer-to-Peer Databases for the Decentralized Web. JavaScript. MIT license. repo. Source: almost 3 years ago
Release: New features for Nalli
I think a wallet-agnostic memo solution is definitely the way. Having wallets that end up (partly) incompatible is only gonna hurt the UX. Maybe a decentralised DB solution like OrbitDB or GunDB can be the best way forward, although I haven't dove deeply into the docs yet. Source: about 3 years ago
Building a decentralized database
Checkout this https://github.com/orbitdb/orbit-db peer-to-peer database for the decentralized Web. Source: about 3 years ago
Any suggestions to build a decentralized web app?
I want to build a decentralized social media web app for a personal project, and I'm thinking on using IPFS. What tool, API, or library can get me set up without writing smart contracts or using blockchain solutions? I've heard that GunDB or OrbitDB are useful libraries- is that true? What are your thoughts and suggestions? Source: over 3 years ago