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DBMS > Amazon SimpleDB vs. Apache Druid vs. Datomic vs. TimescaleDB

System Properties Comparison Amazon SimpleDB vs. Apache Druid vs. Datomic vs. TimescaleDB

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache Druid  Xexclude from comparisonDatomic  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 ScioreOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelKey-value storeRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteaws.amazon.com/­simpledbdruid.apache.orgwww.datomic.comwww.timescale.com
Technical documentationdocs.aws.amazon.com/­simpledbdruid.apache.org/­docs/­latest/­designdocs.datomic.comdocs.timescale.com
DeveloperAmazonApache Software Foundation and contributorsCognitectTimescale
Initial release2007201220122017
Current release29.0.1, April 20241.0.6735, June 20232.15.0, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache license v2commercial infolimited edition freeOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureC
Server operating systemshostedLinux
OS X
Unix
All OS with a Java VMLinux
OS X
Windows
Data schemeschema-freeyes infoschema-less columns are supportedyesyes
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.nonoyes
Secondary indexesyes infoAll columns are indexed automaticallyyesyesyes
SQL infoSupport of SQLnoSQL for queryingnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsRESTful HTTP APIJDBC
RESTful HTTP/JSON API
RESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
Clojure
JavaScript
PHP
Python
R
Ruby
Scala
Clojure
Java
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoyes infoTransaction Functionsuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
TriggersnonoBy using transaction functionsyes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationSharding infomanual/auto, time-basednone infoBut extensive use of caching in the application peersyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, via HDFS, S3 or other storage enginesnone infoBut extensive use of caching in the application peersSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
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 datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)RBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnofine grained access rights according to SQL-standard

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More resources
Amazon SimpleDBApache DruidDatomicTimescaleDB
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