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DBMS > Hazelcast vs. Prometheus vs. RDF4J vs. Sqrrl vs. Teradata Aster

System Properties Comparison Hazelcast vs. Prometheus vs. RDF4J vs. Sqrrl vs. Teradata Aster

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonPrometheus  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSqrrl  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Sqrrl has been acquired by Amazon and became a part of Amazon Web Services. It has been removed from the DB-Engines ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionA widely adopted in-memory data gridOpen-source Time Series DBMS and monitoring systemRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Adaptable, secure NoSQL built on Apache AccumuloPlatform for big data analytics on multistructured data sources and types
Primary database modelKey-value storeTime Series DBMSRDF storeDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.72
Rank#59  Overall
#6  Key-value stores
Score7.56
Rank#49  Overall
#3  Time Series DBMS
Score0.72
Rank#222  Overall
#9  RDF stores
Websitehazelcast.comprometheus.iordf4j.orgsqrrl.com
Technical documentationhazelcast.org/­imdg/­docsprometheus.io/­docsrdf4j.org/­documentation
DeveloperHazelcastSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Amazon infooriginally Sqrrl Data, Inc.Teradata
Initial release20082015200420122005
Current release5.3.6, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoJavaJava
Server operating systemsAll OS with a Java VMLinux
Windows
Linux
OS X
Unix
Windows
LinuxLinux
Data schemeschema-freeyesyes infoRDF Schemasschema-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 dateyesNumeric data onlyyesyesyes
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 strategyno infoImport of XML data possibleyes infoin Aster File Store
Secondary indexesyesnoyesyesyes
SQL infoSupport of SQLSQL-like query languagenononoyes
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP/JSON APIJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Accumulo Shell
Java API
JDBC
ODBC
RESTful HTTP API
Thrift
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
PHP
Python
Actionscript
C infousing GLib
C#
C++
Cocoa
Delphi
Erlang
Go
Haskell
Java
JavaScript
OCaml
Perl
PHP
Python
Ruby
Smalltalk
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesnoyesnoR packages
Triggersyes infoEventsnoyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding infomaking use of HadoopSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated Mapyes infoby Federationnoneselectable replication factor infomaking use of Hadoopyes 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 methodsyesnonoyesyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmnoneImmediate Consistency infoDocument store kept consistent with combination of global timestamping, row-level transactions, and server-side consistency resolution.Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitednoACID infoIsolation support depends on the API usedAtomic updates per row, document, or graph entityACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlRole-based access controlnonoCell-level Security, Data-Centric Security, Role-Based Access Control (RBAC), Attribute-Based Access Control (ABAC)fine grained access rights according to SQL-standard

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More resources
HazelcastPrometheusRDF4J infoformerly known as SesameSqrrlTeradata Aster
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