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DBMS > Hawkular Metrics vs. Pinecone vs. Postgres-XL vs. Tarantool

System Properties Comparison Hawkular Metrics vs. Pinecone vs. Postgres-XL vs. Tarantool

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonPinecone  Xexclude from comparisonPostgres-XL  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.A managed, cloud-native vector databaseBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelTime Series DBMSVector DBMSRelational DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Score3.23
Rank#92  Overall
#3  Vector DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitewww.hawkular.orgwww.pinecone.iowww.postgres-xl.orgwww.tarantool.io
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.pinecone.io/­docs/­overviewwww.postgres-xl.org/­documentationwww.tarantool.io/­en/­doc
DeveloperCommunity supported by Red HatPinecone Systems, IncVK
Initial release201420192014 infosince 2012, originally named StormDB2008
Current release10 R1, October 20182.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoMozilla public licenseOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC and C++
Server operating systemsLinux
OS X
Windows
hostedLinux
macOS
BSD
Linux
macOS
Data schemeschema-freeyesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesString, Number, Booleanyesstring, 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.nonoyes infoXML type, but no XML query functionalityno
Secondary indexesnoyesyes
SQL infoSupport of SQLnonoyes infodistributed, parallel query executionFull-featured ANSI SQL support
APIs and other access methodsHTTP RESTRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Open binary protocol
Supported programming languagesGo
Java
Python
Ruby
Python.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnouser defined functionsLua, C and SQL stored procedures
Triggersyes infovia Hawkular Alertingyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on Cassandrahorizontal partitioningSharding, 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 nodesselectable replication factor infobased on CassandraAsynchronous 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 systemEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyCasual 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 integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoMVCCACID, 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 persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlnofine grained access rights according to SQL-standardAccess 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
Hawkular MetricsPineconePostgres-XLTarantool
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