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

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

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Editorial information provided by DB-Engines
NameHawkular Metrics  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  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.Data warehouse and analytics appliance part of IBM PureSystemsBased 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 DBMSRelational 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
Score8.59
Rank#45  Overall
#29  Relational 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.ibm.com/­products/­netezzawww.postgres-xl.orgwww.tarantool.io
Technical documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guidewww.postgres-xl.org/­documentationwww.tarantool.io/­en/­doc
DeveloperCommunity supported by Red HatIBMVK
Initial release201420002014 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 servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC and C++
Server operating systemsLinux
OS X
Windows
Linux infoincluded in applianceLinux
macOS
BSD
Linux
macOS
Data schemeschema-freeyesyesFlexible 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.noyes infoXML type, but no XML query functionalityno
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnoyesyes infodistributed, parallel query executionFull-featured ANSI SQL support
APIs and other access methodsHTTP RESTJDBC
ODBC
OLE DB
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Open binary protocol
Supported programming languagesGo
Java
Python
Ruby
C
C++
Fortran
Java
Lua
Perl
Python
R
.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 proceduresnoyesuser defined functionsLua, C and SQL stored procedures
Triggersyes infovia Hawkular Alertingnoyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesSharding infobased on CassandraShardinghorizontal 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 CassandraSource-replica replicationAsynchronous 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 methodsnoyesno
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 integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID 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.nonoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlnoUsers with fine-grained authorization conceptfine 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 MetricsNetezza infoAlso called PureData System for Analytics by IBMPostgres-XLTarantool
DB-Engines blog posts

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

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