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DBMS > Coveo vs. Hawkular Metrics vs. RDF4J vs. Tarantool

System Properties Comparison Coveo vs. Hawkular Metrics vs. RDF4J vs. Tarantool

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Editorial information provided by DB-Engines
NameCoveo  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.In-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelSearch engineTime Series DBMSRDF storeDocument store
Key-value store
Relational DBMS
Secondary database modelsSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.11
Rank#118  Overall
#11  Search engines
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score0.74
Rank#222  Overall
#9  RDF stores
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.coveo.comwww.hawkular.orgrdf4j.orgwww.tarantool.io
Technical documentationdocs.coveo.comwww.hawkular.org/­hawkular-metrics/­docs/­user-guiderdf4j.org/­documentationwww.tarantool.io/­en/­doc
DeveloperCoveoCommunity supported by Red HatSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.VK
Initial release2012201420042008
Current release2.10.0, May 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoEclipse Distribution License (EDL), v1.0.Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Unix
Windows
BSD
Linux
macOS
Data schemehybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationschema-freeyes infoRDF SchemasFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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.nonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnononoFull-featured ANSI SQL support
APIs and other access methodsRESTful HTTP APIHTTP RESTJava API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
Open binary protocol
Supported programming languagesC#
Java
JavaScript
Python
Go
Java
Python
Ruby
Java
PHP
Python
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnonoyesLua, C and SQL stored procedures
Triggersyesyes infovia Hawkular Alertingyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesyesSharding infobased on CassandranoneSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on CassandranoneAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Casual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID infoIsolation support depends on the API usedACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlgranular access controls, API key management, content filtersnonoAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles

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More resources
CoveoHawkular MetricsRDF4J infoformerly known as SesameTarantool
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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