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DBMS > GigaSpaces vs. Hawkular Metrics vs. Memcached vs. Microsoft Azure Synapse Analytics vs. TimescaleDB

System Properties Comparison GigaSpaces vs. Hawkular Metrics vs. Memcached vs. Microsoft Azure Synapse Analytics vs. TimescaleDB

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonMemcached  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.In-memory key-value store, originally intended for cachingElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSKey-value storeRelational DBMSTime Series DBMS
Secondary database modelsGraph DBMS
Search engine
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score19.42
Rank#32  Overall
#4  Key-value stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.gigaspaces.comwww.hawkular.orgwww.memcached.orgazure.microsoft.com/­services/­synapse-analyticswww.timescale.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidegithub.com/­memcached/­memcached/­wikidocs.microsoft.com/­azure/­synapse-analyticsdocs.timescale.com
DeveloperGigaspaces TechnologiesCommunity supported by Red HatDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoftTimescale
Initial release20002014200320162017
Current release15.5, September 20201.6.25, March 20242.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0Open Source infoBSD licensecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetJavaCC++C
Server operating systemsLinux
macOS
Solaris
Windows
Linux
OS X
Windows
FreeBSD
Linux
OS X
Unix
Windows
hostedLinux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesnoyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.no infoXML can be used for describing objects metadatanonoyes
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLSQL-99 for query and DML statementsnonoyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
HTTP RESTProprietary protocolADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C++
Java
Python
Scala
Go
Java
Python
Ruby
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C#
Java
PHP
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnonoTransact SQLuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes, event driven architectureyes infovia Hawkular Alertingnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandranoneSharding, horizontal partitioningyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
selectable replication factor infobased on Cassandranone infoRepcached, a Memcached patch, provides this functionallityyesSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesnoyesyes
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 controlnoyes infousing SASL (Simple Authentication and Security Layer) protocolyesfine grained access rights according to SQL-standard

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More resources
GigaSpacesHawkular MetricsMemcachedMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTimescaleDB
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