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Oracle TimesTen VS Datahike

Compare Oracle TimesTen VS Datahike and see what are their differences

Oracle TimesTen logo Oracle TimesTen

TimesTen is an in-memory, relational database management system with persistence and...

Datahike logo Datahike

A durable datalog database adaptable for distribution.
  • Oracle TimesTen Landing page
    Landing page //
    2023-06-17
  • Datahike Landing page
    Landing page //
    2023-08-22

Oracle TimesTen features and specs

  • High Performance
    Oracle TimesTen is an in-memory database providing extremely fast data access and transaction processing, which is beneficial for applications that require real-time performance.
  • Low Latency
    Since the database is stored in memory, data retrieval and manipulation are very quick, reducing latency significantly compared to disk-based databases.
  • Scalability
    TimesTen can be easily scaled to handle large volumes of data and transaction loads, supporting hybrid configurations with Oracle Database to extend scalability and reliability.
  • SQL Compatibility
    It supports SQL and PL/SQL, making it easier for developers experienced with Oracle databases to use TimesTen without a steep learning curve.
  • High Availability
    TimesTen offers features like replication and failover for high availability which is crucial for mission-critical applications.
  • Integration with Oracle Ecosystem
    TimesTen integrates well with other tools and products in the Oracle ecosystem, allowing for seamless operations across different Oracle platforms.

Possible disadvantages of Oracle TimesTen

  • Cost
    Oracle TimesTen can be expensive compared to some of its open-source alternatives, making it less attractive for smaller businesses or projects with limited budgets.
  • Hardware Dependency
    Being an in-memory database, it requires machines with large RAM capacities to store substantial datasets, which can be a limiting factor.
  • Complexity
    Setting up and managing TimesTen can be complex, especially when trying to optimize for performance and ensure data consistency across systems.
  • Limited Community Support
    Unlike more popular database systems, the community support for TimesTen is limited, which means troubleshooting and problem-solving might not be as straightforward.
  • Data Volatility
    Since TimesTen stores data in memory, there’s a risk of data loss in the event of power failures, despite having persistence features to mitigate this risk.

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.

Oracle TimesTen videos

My demo of Oracle TimesTen in memory DB with Free Developer Day tools with a VirtualBox VM appliance

Datahike videos

No Datahike videos yet. You could help us improve this page by suggesting one.

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Category Popularity

0-100% (relative to Oracle TimesTen and Datahike)
Databases
49 49%
51% 51
Relational Databases
51 51%
49% 49
Network & Admin
49 49%
51% 51
NoSQL Databases
53 53%
47% 47

User comments

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Social recommendations and mentions

Based on our record, Datahike seems to be more popular. It has been mentiond 4 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.

Oracle TimesTen mentions (0)

We have not tracked any mentions of Oracle TimesTen yet. Tracking of Oracle TimesTen recommendations started around Mar 2021.

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

What are some alternatives?

When comparing Oracle TimesTen and Datahike, you can also consider the following products

Valentina Server - Valentina Server is 3 in 1: Valentina DB Server / SQLite Server / Report Server

Datomic - The fully transactional, cloud-ready, distributed database

MarkLogic Server - MarkLogic Server is a multi-model database that has both NoSQL and trusted enterprise data management capabilities.

PlanetScale - The last database you'll ever need. Go from idea to IPO.

Matisse - Matisse is a post-relational SQL database.

EdgeDB - EdgeDB is a next-generation graph-relational database that lets you easily build flexible, scalable applications in real-time.