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DBMS > FoundationDB vs. Hazelcast vs. Microsoft Azure Table Storage vs. Teradata Aster

System Properties Comparison FoundationDB vs. Hazelcast vs. Microsoft Azure Table Storage vs. Teradata Aster

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Editorial information provided by DB-Engines
NameFoundationDB  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionOrdered key-value store. Core features are complimented by layers.A widely adopted in-memory data gridA Wide Column Store for rapid development using massive semi-structured datasetsPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Key-value storeWide column storeRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.06
Rank#185  Overall
#31  Document stores
#28  Key-value stores
#85  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score4.04
Rank#77  Overall
#6  Wide column stores
Websitegithub.com/­apple/­foundationdbhazelcast.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationapple.github.io/­foundationdbhazelcast.org/­imdg/­docs
DeveloperFoundationDBHazelcastMicrosoftTeradata
Initial release2013200820122005
Current release6.2.28, November 20205.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2; commercial licenses availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemsLinux
OS X
Windows
All OS with a Java VMhostedLinux
Data schemeschema-free infosome layers support schemasschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateno infosome layers support typingyesyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yes infothe object must implement a serialization strategynoyes infoin Aster File Store
Secondary indexesnoyesnoyes
SQL infoSupport of SQLsupported in specific SQL layer onlySQL-like query languagenoyes
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP APIADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresin SQL-layer onlyyes infoEvent Listeners, Executor ServicesnoR packages
Triggersnoyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infoReplicated Mapyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemLinearizable consistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityin SQL-layer onlynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitedoptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnoRole-based access controlAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard

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More resources
FoundationDBHazelcastMicrosoft Azure Table StorageTeradata Aster
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