TCache alternatives and similar packages
Based on the "Data" category.
Alternatively, view TCache alternatives based on common mentions on social networks and blogs.
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lens
Lenses, Folds, and Traversals - Join us on web.libera.chat #haskell-lens -
semantic-source
Parsing, analyzing, and comparing source code across many languages -
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text
Haskell library for space- and time-efficient operations over Unicode text. -
code-builder
Packages for defining APIs, running them, generating client code and documentation. -
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compendium-client
Mu (μ) is a purely functional framework for building micro services. -
cassava
A CSV parsing and encoding library optimized for ease of use and high performance -
holmes
A reference library for constraint-solving with propagators and CDCL. -
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resource-pool
A high-performance striped resource pooling implementation for Haskell -
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primitive
This package provides various primitive memory-related operations. -
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discrimination
Fast linear time sorting and discrimination for a large class of data types -
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reflection
Reifies arbitrary Haskell terms into types that can be reflected back into terms -
IORefCAS
A collection of different packages for CAS based data structures. -
dependent-map
Dependently-typed finite maps (partial dependent products) -
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dependent-sum
Dependent sums and supporting typeclasses for comparing and displaying them -
orgmode-parse
Attoparsec parser combinators for parsing org-mode structured text! -
scientific
Arbitrary-precision floating-point numbers represented using scientific notation -
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streaming
An optimized general monad transformer for streaming applications, with a simple prelude of functions -
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text-icu
This package provides the Haskell Data.Text.ICU library, for performing complex manipulation of Unicode text. -
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Access the most powerful time series database as a service
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README
TCache
TCache is a transactional cache written in Haskell with configurable persistence. It allows conventional STM transactions for objects that synchronize with a user-defined storage. State is kept synchronized between memory and permanent storage via transactions. Default persistence is via files, and is provided for testing purposes.
0.9.0.4 : Solves a bug in the management of weak pointers that evaporated registers from the cache 0.9.0.3 : Solves a lost registers bug. 0.9.0.1 : Solves a bug when object keys generate invalid filenames, and includes changes in defaultPersistence to further separate serialization from input-output.
0.9: Introduces full text search. Also adjusts serialization so it is achieved through byteStrings.
This version supports backward compatibility and also permits transparent retrieval of and transactions between objects without directly using STM references. It now provides explicit STM persistent references (DBRefs) that leverage clean, traditional haskell reference syntax for performing database transactions.
DBRefs are essentially persistent TVars indexed in the cache using a traditional readDBRef/writeDBRef Haskell interface like that of the STM Monad. Additionally, because DBRefs are serializable, they can be embedded in serializable registers. As they are references this means they point to other serializable registers. This enables persistent, mutable and efficient inter-object relations.
Triggers are also included in this release. These are user defined hooks that get called on register updates. They can be used for making the actualization of inter-object relations easier, and also permit higher-level customizable accesses. The query language internally uses triggers for its indexing.
This version also implements a straight-forward, non-intrusive, type-safe pure Haskell query language that is based on register field relations. This module can be imported separately. See Data.TCache.IndexQuery for further information.
The file persistence implementation is more reliable as IO reads are now in STM transactions.
To ease the implementation of other user-defined persistence, Data.TCache.DefaultPersistence needs to be imported explicitly for deriving file persistence instances.
The 0.9 version adds full-text indexing and search, which is incorporated into the experimental query language.
It also changes the default Persistence mechanism. Now ByteStrings are used for serialization and deserialization. A Serializable class and a Persist structure decouples serialization from ByteString and read/write to files. Both can be redefined separately, so the default persistence could be changed with setPersist to write to blobs in a databases, for example. Default persistence now no longer has to be in files.