Datomic

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Discussion of Datomic On-Prem Datomic On-Prem covers all of Datomic Enterprise, Datomic Pro, Datomic Starter, and Datomic Free. A Datomic deployment consists of a storage Datomic Pro and Datomic Cloud are FREE! Products. Datomic Pro Datomic Cloud. Support Pricing. Datomic Pro Pricing Datomic Cloud Pricing. Resources. Datomic Docs. Product

Datomic - Datomic Ions: Your App on Datomic Cloud

That supports Java 8 or later. For Datomic On-Prem, you’ll need a server or servers to host the transactor and peers. For Datomic Cloud, you’ll need an AWS account and access to the necessary AWS services. How does Datomic handle data consistency? Datomic provides strong consistency through its use of an ACID-compliant transaction model. All transactions are serialized through a single transactor, ensuring that all reads and writes are consistent across the entire database. Can I migrate my data from Datomic On-Prem to Datomic Cloud? Yes, Datomic provides tools and documentation to help you migrate your data from Datomic On-Prem to Datomic Cloud. The process involves exporting your data from the On-Prem version and importing it into the Cloud version. What kind of support is available for Datomic? Datomic offers a range of support options, including documentation, tutorials, and a community forum. For customers with a paid license, Datomic also offers direct support from its team of experts. How does Datomic handle backups and data recovery? Datomic has built-in support for backups and data recovery. For Datomic On-Prem, you can configure automatic backups to a storage location of your choice. For Datomic Cloud, backups are automatically stored in AWS S3. What programming languages can I use with Datomic? Datomic is designed to work with the Clojure programming language, but it also provides APIs for Java and other JVM languages. Additionally, you can use Datomic’s REST API to interact with the database from any language that can make HTTP requests. How does Datomic handle scaling? Datomic’s architecture allows it to scale horizontally by adding more peers. For Datomic Cloud, scaling is handled automatically by AWS. For Datomic On-Prem, you can add more peers to handle increased read load, and you can add more transactors to handle increased write load.

Datomic Analytics: Datomic Client Exception - Troubleshooting - Datomic

Not be necessary for the read-only infrastructure, but the Transactor will need some type of sharding mechanism, once it has to deal with heavy loads.● The Datomic Pro pricing is quite restricting, and considering that Datomic Free is no good for any kind of production use, building some experimental projects will be pretty hard for the average developer.Alex Popescu wrote a great post on Datomic, focusing on these critical points and some more.ConclusionI personally think that many of the concepts and ideas behind Datomic, especially making time a first-class citizen, are great and bear a lot of potential. But I can’t see me using it in the near future, because I’d like to prove some of the team’s performance claims for myself, a desire not in keeping with my finances relative to a Pro license.Otherwise, some of Datomic’s advanced features, like fulltext search, multiple data-sources (besides the distributed storage service) and the possibility to use the system for local data-processing only, could potentially be useful.Please share any thoughts you might have in the comments!Dive deeper○ The Datomic Rationale○ A few great videos on Datomic○ Back to the Future with Datomic○ Datomic: Initial Analysis (comparing Datomic to other DBMS)Frequently Asked Questions (FAQs) about DatomicWhat is the difference between Datomic On-Prem and Datomic Cloud? Datomic On-Prem and Datomic Cloud are two different deployment models for the Datomic database system. Datomic On-Prem is designed to be installed and run on your own servers or in a data center of your choice. It provides you with full control over your data and infrastructure. On the other hand, Datomic Cloud is a fully managed service that runs on AWS (Amazon Web Services). It provides automatic scaling, backups, and failover, reducing the operational overhead. How is Datomic priced? Datomic has different pricing models for its On-Prem and Cloud versions. For Datomic On-Prem, you pay a one-time license fee based on the number of peers and transactors. For Datomic Cloud, you pay based on the AWS resources consumed, which can vary depending on your usage and the specific AWS services you use. Is there a free version of Datomic? Yes, Datomic offers a free version known as Datomic Free. It’s a fully functional version of Datomic that’s limited to a single transactor and two peers. It’s ideal for development, testing, and small production deployments. What are the system requirements for Datomic? Datomic can run on any system

Datomic - Datomic Editions and Pricing

This is the first article in an occasional series on interesting database technologies oustide the (No)SQL mainstream. I will introduce you to the core concepts of these DBMS, share some thoughts on them and tell you where to find more information.Most of this is not intended for immediate use in your next project: rather, I want to provide inspiration and communicate interesting new takes on the problems in this field. But if, someday, one of those underdogs becomes the status quo, you can tell everyone that you knew it before it was cool …All jokes aside, I hope you’ll enjoy these. Let’s get started.Key TakeawaysDatomic is a novel database management system (DBMS) that incorporates a fact-based, time-sensitive data model with support for ACID transactions and JOINs, developed by Rich Hickey, the creator of Clojure.Datomic’s architecture is unique in that it separates data storage and processing, with the client handling complex data processing and the Transactor managing ACID transactions, data synchronization, and indexing.Data in Datomic is represented as immutable facts called “Datoms”, which are composed of an entity, attribute, value, and transaction timestamp. This system allows for time-sensitive queries and preserves all information, unlike traditional databases that overwrite old data with new.Datomic’s query language, Datalog, enables users to run queries on both current and historical data, as well as simulate queries on hypothetical future data.While Datomic’s innovative ideas offer potential benefits, concerns have been raised about the separation of data and processing, the Transactor component as a potential single point of failure and bottleneck, and the high cost of the Datomic Pro version.OverviewDatomic is the latest brain-child of Rich Hickey, the creator of Clojure. It was released earlier this year and is basically a new type of DBMS that incorporates his ideas about how today’s databases should work. It’s an elastically scalable, fact-based, time-sensitive database with support for ACID transactions and JOINs.Here are the core aspects this interesting piece of technology revolves around:A novel architecture. Peers, Apps and the Transactor.A fact-based data-model.A powerful, declarative query language, “Datalog”.The Datomic team wants its DBMS to provide the first, “real” record implementation: records in the pre-computer age preserved information about the past, whereas in todays databases old data is only overwritten with new. Datomic changes that, and preserves all information, differentiating between information by making time an integral part of the system.1. A novel architectureThe single most revolutionary thing about Datomic would be its. Discussion of Datomic On-Prem Datomic On-Prem covers all of Datomic Enterprise, Datomic Pro, Datomic Starter, and Datomic Free. A Datomic deployment consists of a storage

Datomic - Datomic is Free - blog.datomic.com

Own local cache of data segments, in memory”, which would require perfect cache synchronisation. Otherwise consistency is only guaranteed for one peer, which quite frankly is pointless. Hopefully, this management overhead won’t neutralize the promising ACID capabilities and the performance gains of in-memory operations.The second quote makes initial sense, but still raises a few concerns:What happens when one Transactor faces too much load? The Datomic team would like to avoid sharding, but wouldn’t exactly that be necessary at some point? Also, even if we pretend that the number of transactions wouldn’t increase with more peers, the time it takes to transmit changes to all of them sure does.In conclusion, the Transactor could be an amazing thing to have with smaller datasets but may become a potential performance bottleneck or Single Point of Failure.Storage servicesThese services handle the distributed storage of data. Some possibilities:● Transactor-Local storage (free, useful for playing with Datomic on a single machine)● SQL Databases (require Datomic Pro)● DynamoDB (require Datomic Pro)● Infinispan Memory Cluster (require Datomic Pro)… plus a few more. Storage service support could be one big reason to try out Datomic, but unfortunately, only the temporary local storage is available for Datomic Free users (aka users who aren’t willing to pay $3,000+ for a brand new DBMS).All in all, the Datomic architecture comes with loads of innovative ideas and potential benefits, but its real-world applicability remains to be proven.Please read the detailed architecture overview in the Datomic documentation or watch this 20 minute video by Mr. Hickey himself.(Original image taken from here.)2. A fact-based data-modelDatomic doesn’t model data as documents, objects or rows in a table. Instead, data is represented as immutable facts called “Datoms”. They are made up of four pieces:EntityAttributeValueTransaction timestampDatoms are highly reminiscent of the subject-predicate-object scheme used in RDF Triplestores.Anything can be a datom:“John’s balance is $12,000” → [john :balance 12000 ]These attribute definitions are the only type of schema implied on the dataset.In a relational database, this would be represented as a 12000 at the “john”-row in the “balance” cell (data is place-oriented). If now, a month later, John’s balance changes to 6,000, this specific cell would be wiped, and the new value would be put in. The fact, that John had 12,000 on his account a month ago is gone forever.One of the main reasons for the creation of Datomic was the feeling, that today’s hardware is finally able

Datomic - A Conversational Introduction to Datomic

A subset of Datomic functionalityand should work as a drop-in replacement on the JVM. The rest of Datahike willbe ported to core.async to coordinate IO in a platform-neutral manner.Refer to the docs for more information:backend developmentbenchmarkinggarbage collectioncontributing to Datahikeconfigurationdifferences to Datomicentity speclogging and error handlingschema flexibilitytime varianceversioningFor simple examples have a look at the projects in the examples folder.Example ProjectsInvoice creationdemonstrated at the Dutch ClojureMeetup.Relationship to Datomic and DataScriptDatahike provides similar functionality to Datomic and canbe used as a drop-in replacement for a subset of it. The goal of Datahike is notto provide an open-source reimplementation of Datomic, but it is part of thereplikativ toolbox aimed to build distributeddata management solutions. We have spoken to many backend engineers and Clojuredevelopers, who tried to stay away from Datomic just because of its proprietarynature and we think in this regard Datahike should make an approach to Datomiceasier and vice-versa people who only want to use the goodness of Datalog insmall scale applications should not worry about setting up and depending onDatomic.Some differences are:Datahike runs locally on one peer. A transactor might be provided in thefuture and can also be realized through any linearizing write mechanism, e.g.Apache Kafka. If you are interested, please contact us.Datahike provides the database as a transparent value, i.e. you can directlyaccess the index datastructures (hitchhiker-tree) and leverage theirpersistent nature for replication. These internals are not guaranteed to staystable, but provide useful insight into what is going on and can be optimized.Datahike supports GDPR compliance by allowing to completely remove database entries.Datomic has a REST interface and a Java APIDatomic provides timeoutsDatomic is a full-fledged scalable database (as a service) built from theauthors of Clojure and people with a lot of experience. If you need this kindof professional support, you should definitely stick to Datomic.Datahike's query engine and most of its codebase come fromDataScript. Without the work onDataScript, Datahike would not have been possible. Differences to Datomic withrespect to the query engine are documented there.When to Choose Datahike vs. Datomic vs. DataScriptDatahikePick Datahike if your app has modest requirements towards a typical durabledatabase, e.g. a single machine and a few millions of entities at maximum.Similarly, if you want to have an open-source solution and be able to study andtinker with the codebase of your database, Datahike provides a comparativelysmall and well composed codebase to tweak it to your needs. You should alsoalways be able to migrate to Datomic later easily.DatomicPick Datomic if you already know that you will need scalability later or if youneed a network API for your database. There is also plenty of material aboutDatomic online already. Most of it applies in some form or another to Datahike,but it might be easier to use Datomic directly when you first learn Datalog.DataScriptPick DataScript if you want the fastest possible query performance and do nothave a huge amount of data. You can easily persist the write operationsseparately and use the fast in-memory index data structure of DataScript then.Datahike also at the moment does not support ClojureScript anymore, although weplan

What is Datomic? - Datomic Knowledgebase

A Datomic transactor or peer needs only the minimum permissions necessary to communicate with various AWS services. These permissions are documented in Setting Up Storage Services.But you still need some way to install these minimal permissions on ephemeral virtual hardware. Early versions of AWS left this problem to the developer. Solutions were tedious and ad hoc, but more important they were risky. Leaving every application developer the task of passing credentials around is a recipe for credentials lying around in a hundred different places (or even checked into source code repositories.)IAM roles provide a generic solution to this problem. From the FAQ: "An IAM role allows you to delegate access, with defined permissions, to trusted entities without having to share long term access keys" (emphasis added). From a developer perspective, IAM roles get credentials out of your application code.ImplementationStarting with version 0.9.4314, Datomic supports IAM roles as the default mechanism for conveying credentials in AWS. What does this mean for developers?If you are configuring Datomic for the first time, the setup instructions will secure peers and transactors using IAM roles. If you have an existing Datomic installation and want to upgrade to roles, Migrating to IAM Roles will walk you through the process.Using explicit credentials in transactor properties and in connection URIs is deprecated, but will continue to work. Your existing deployments will not break.IAM roles make your application both easier to manage and more secure. Use them...

What is a datom? - Datomic Knowledgebase

Architecture. Datomic puts the brain of your app back into the client. In a traditional setup, the server handles everything from queries and transactions to actually storing the data. With increasing load, more servers are added and the dataset is sharded across these. As most of todays NoSQL databases show, this method works very well, but comes at the cost of some “brain”, as Mr. Hickey argues. The loss of consistency and/or query-power is a well-known tradeoff for scale.To achieve distributed storage, but with a powerful query language and consistent transactions, Datomic leverages existing scalable databases as simple distributed storage services. All the complex data processing is handled by the application itself. Almost as in a native desktop application (if you can remember one of those).This brings us to the first cornerstone of the Datomic infrastructure:The Peer ApplicationA peer is created by embedding the Datomic library into your client-code. From then, every instance of your application will be able to:● communicate with the Transactor and storage services● run Datalog queries, access data and handle caching of the working setEvery peer manages its own working-set of data in memory and synchronizes with a “Live Index” of the global dataset. This allows the application to run very flexible queries without the need for roundtrips (more on that under “Criticism”).But so far, we’ve only got back query power. To also re-enable consistent transactions, Datomic takes a step further: it makes the storage service read-only and forces all writes through a new kind of architectural component, the “Transactor”.The TransactorThe Transactor will:● handle ACID transactions● synchronously write to redundant storage● communicate changes to Peers● indexing your dataset in the backgroundIt seems as if the Datomic Team banished everything that made Relational DBMS hard to scale in a separate module, and tried not to worry too hard about it. For example, the Datomic-Rationale states:“When reads are separated from writes, writes are never held up by queries. In the Datomic architecture, the transactor is dedicated to transactions, and need not service reads at all!”and“Putting query engines in peers makes query capability as elastic as the applications themselves. In addition, putting query engines into the applications themselves means they never wait on each other’s queries.”The first statement is true for some read-operations, but I couldn’t find a hint as to how the Transactor handles reads in transactions. Though it is mentioned that “Each peer and transactor manages its. Discussion of Datomic On-Prem Datomic On-Prem covers all of Datomic Enterprise, Datomic Pro, Datomic Starter, and Datomic Free. A Datomic deployment consists of a storage

Datomic-free being out-phased? - Datomic Pro - Datomic

Built a variety of powerful systems, taking advantage ofACID transactionspluggable SQL/NoSQL/cloud storagecomplete access to the history of informationthe Datalog query languageelastic read scalabilitya granular information modelOver the course of the year, we produced over 40 Datomic releases. The API has been remarkably stable: Our commitment to a strong architecture has allowed us to focus on adding features and fleshing out the vision, without the churn of revisiting past decisions. A major new feature is the Datomic Console, a graphical UI for exploring Datomic databases. The console provides a great visual introduction to the Datomic information model. It supports exploring schema, building and executing queries, navigating entities, examining transaction history, and walking raw indexes. We made several API additions:Excision, a sound model (and API) for permanent removal of data, with auditability.The log API provides the ability to access the log, which is more properly viewed as a time index.The seekDatoms and entidAt APIs provide advanced capability for accessing Datomic's indexes, augmenting the datoms API.The sync API allows multiple processes to coordinate around points in time-of-record, or relative to local process time.Transaction map expansion automates the creation of arbitrarily nested data.We also made a number of operational improvements:We added Cassandra and to the list of supported storage, in addition to the existing options of DynamoDB, SQL, filesystem, CouchBase, Infinispan, and Riak.The Starter Edition of the Datomic Pro license makes all storages available, for free.We have added a number of new CloudWatch metrics, and a pluggable metrics API for integration with other systems.The MusicBrainz sample database is a great dataset for exploring Datomic.We continue to track AWS best practices, now supporting IAM roles for distributing credentials and DynamoDB local for testing.We are looking forward to an equally exciting 2014. We will be delivering a number of new features requested by users, plus a few big surprises. Many thanks to our customers and early adopters for your support and feedback.Happy New Year!.. 18 November 2013 We are pleased to announce alpha support for Cassandra as a storage service for Datomic, now available in version 0.9.4384.Cassandra is an elastically scalable, distributed, redundant and highly-available column store. Recent versions of Cassandra added support for compare-and-swap operations via lightweighttransactions using an implementation of the Paxos protocol. Datomic leverages this mechanism to manage a small number of keys per database that require coordinated access, while the bulk of a database's content is written as immutable data to a quorum of replicas in the cluster.Cassandra support requires a minimum Apache Cassandra 2.0.2 or newer, or equivalent. Native CQL protocol support must be enabled. Cross-data center deployments are not supported. Cassandra internal security is supported, but optional.This release represents preliminary support based on requests from users. We are very interested in feedback.For instructions on configuring Cassandra for use with Datomic, see Setting Up Storage Services... 25 October 2013 With today's Datomic release, you can use IAM roles to manage permissions when running in AWS.MotivationDatomic's AWS support has been designed according to the principle of least privilege. When running in AWS,

Datomic - Datomic MusicBrainz sample database

To keep true records of data, something no other popular DBMS to date does. Datomic never updates data, it simply writes the new facts and keeps the old ones. This paves the way for lots of interesting, time-sensitive queries.Because of its immutable, fact-based nature, Datomic would handle John’s new balance by simply inserting a new fact:[john :balance 6000 ] Facts are never lost. If John is interested in his current balance, he queries for the most recent Datom. But nothing would prevent him to query his complete balance-history anytime he wants. Besides, Datoms are, as the name implies, atomic, the highest possible form of normalization. You can express your data-model in as many entities as you want, the bigger picture is automatically constructed via implicit JOINS.Other benefits● Support for sparse, irregular or hierarchical data○ Attribute values can be references to other entities● Native support for multi-valued attributes● No enforced schema● No need to store data history separately, time is an integral part of datomicSuch flexibility allows Datomic to function as almost anything, for example a complete graph API.Some fallbacks of this approach:● Not suited for large, dynamic data○ As updates are always written as new datoms with a more recent timestamp, large, dynamic blobs of data would soon fill up quite a bit of space● Flexible schemes tend to lead to rashness○ Some planning should still be done on the data-model● Attribute conflicts○ Namespacing should be employed right from the beginning3. Datalog, the finder of lost factsDatomic queries are made up of “WHERE”, “FIND” and “IN” clauses, and a set of rules to apply to facts. The query processor then finds all matching facts in the database, taking into account implicit informationRules are “fact-templates”, which all facts in the database are matched against.Explicit rules could be something like: [?entity :age 42]Implicit rules look like variable bindings: [?entity :age ?a]and can be combined with LISP/Clojure-like expressions: [ (A rule-set to match customers of age > 40 who bought product p would look like this: [?customer :age ?a] [ (> ?a 40) ] [?customer :bought p]The rule-sets are then embedded into the basic query-skeleton: [:find :where ] is just the set of variables you want to have included in your results. We are only interested in the customer, not in his age, so our customer query would look like this: [:find ?customer :where [?customer :age ?a] [(> ?a 40)] [?customer :bought p]]We. Discussion of Datomic On-Prem Datomic On-Prem covers all of Datomic Enterprise, Datomic Pro, Datomic Starter, and Datomic Free. A Datomic deployment consists of a storage Datomic Pro and Datomic Cloud are FREE! Products. Datomic Pro Datomic Cloud. Support Pricing. Datomic Pro Pricing Datomic Cloud Pricing. Resources. Datomic Docs. Product

Healthcheck - Datomic Pro - Datomic Developers

Now run this via: Peer.q(query)This syntax will probably take some getting used to (except you’re familiar with Clojure), but I find it to be very readable and, as the Datomic Rationale promises, “meaning is evident”.Querying the pastTo run your queries on your fact-history, no change in the query string is required: Peer.q(query, db.asOf()You can also simulate your query on hypothetical, new data. Kind of like a predictive query about the future: Peer.q(query, db.with())For more information on the query – syntax, please refer to the very good documentation and this video.Use casesDatomic is certainly not here to kill every other DBMS, but it’s an interesting match for some applications. The one that came to my mind first was analytics:● Facts are immutable, non-ACID writes should be fast, as analytics systems usually won’t require strong consistency● Facts are time-sensitive. This is quite interesting for analytics.Status messages, tweets or prices could also be stored much more naturally with regard to their dynamic nature. Also, since this DBMS was explicitly constructed to provide “real” records, everything record related should be an obvious fit.In general, Datomic’s time-sensitive layer provides an interesting twist to your existing dataset. It can be used as a normal DBMS, with an additional dimension of insight. Imagine your e-commerce database including the complete price-history of every item and the engagement history of every customer. Wouldn’t it be fascinating to get a quick answer for otherwise complex questions? “When did this product became popular? – Oh it was after the 10$ price-drop.” “When did this customer started using the site every day? – That was two months ago, here is a graph of his daily time-on-page increase”.CriticismRevolutionary ideas, like the ones Datomic is based on, should always be appreciated, but analysed from multiple angles. The technology is too young to make a final judgement but some early criticism includes:● Separation of data and processing.All required data has to be moved to the client application, before it can be processed/queried. This might pose a problem once you get to larger datasets. Local cache will also inevitably constrain working-set growth. Once this upper-bound is passed, round-trips to the server-backend will be necessary again, with even bigger performance penalties. The Datomic team expects it’s approach to “work for most common use cases”, but this can’t be verified at this early stage.● The Transactor component as a Single Point of Failure and a bottleneck● Sharding might