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DBMS > Amazon SimpleDB vs. Hawkular Metrics vs. Splice Machine vs. TimescaleDB

System Properties Comparison Amazon SimpleDB vs. Hawkular Metrics vs. Splice Machine vs. TimescaleDB

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSplice Machine  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value storeTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#139  Overall
#24  Key-value stores
Score0.04
Rank#374  Overall
#38  Time Series DBMS
Score0.54
Rank#255  Overall
#116  Relational DBMS
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Websiteaws.amazon.com/­simpledbwww.hawkular.orgsplicemachine.comwww.timescale.com
Technical documentationdocs.aws.amazon.com/­simpledbwww.hawkular.org/­hawkular-metrics/­docs/­user-guidesplicemachine.com/­how-it-worksdocs.timescale.com
DeveloperAmazonCommunity supported by Red HatSplice MachineTimescale
Initial release2007201420142017
Current release3.1, March 20212.13.0, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesnumerics, 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.noyes
Secondary indexesyes infoAll columns are indexed automaticallynoyesyes
SQL infoSupport of SQLnonoyesyes infofull PostgreSQL SQL syntax
APIs and other access methodsRESTful HTTP APIHTTP RESTJDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
Go
Java
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoyes infoJavauser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyes infovia Hawkular Alertingyesyes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationSharding infobased on CassandraShared Nothhing Auto-Sharding, Columnar Partitioningyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infobased on CassandraMulti-source replication
Source-replica replication
Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)noAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Amazon SimpleDBHawkular MetricsSplice MachineTimescaleDB
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