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DBMS > Amazon SimpleDB vs. Databricks vs. Drizzle vs. HarperDB vs. Kinetica

System Properties Comparison Amazon SimpleDB vs. Databricks vs. Drizzle vs. HarperDB vs. Kinetica

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonDatabricks  Xexclude from comparisonDrizzle  Xexclude from comparisonHarperDB  Xexclude from comparisonKinetica  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.Fully vectorized database across both GPUs and CPUs
Primary database modelKey-value storeDocument store
Relational DBMS
Relational DBMSDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#138  Overall
#24  Key-value stores
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteaws.amazon.com/­simpledbwww.databricks.comwww.harperdb.iowww.kinetica.com
Technical documentationdocs.aws.amazon.com/­simpledbdocs.databricks.comdocs.harperdb.io/­docsdocs.kinetica.com
DeveloperAmazonDatabricksDrizzle project, originally started by Brian AkerHarperDBKinetica
Initial release20072013200820172012
Current release7.2.4, September 20123.1, August 20217.1, August 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGNU GPLcommercial infofree community edition availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Node.jsC, C++
Server operating systemshostedhostedFreeBSD
Linux
OS X
Linux
OS X
Linux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesdynamic schemayes
Typing infopredefined data types such as float or datenoyesyes infoJSON data typesyes
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.yesnono
Secondary indexesyes infoAll columns are indexed automaticallyyesyesyesyes
SQL infoSupport of SQLnowith Databricks SQLyes infowith proprietary extensionsSQL-like data manipulation statementsSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
RESTful HTTP API
JDBCJDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
Python
R
Scala
C
C++
Java
PHP
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnoCustom Functions infosince release 3.1user defined functions
Triggersnono infohooks for callbacks inside the server can be used.noyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replication
Source-replica replication
yes infothe nodes on which a table resides can be definedSource-replica replication
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 or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDACIDAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using LMDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Pluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users and rolesAccess rights for users and roles on table level
More information provided by the system vendor
Amazon SimpleDBDatabricksDrizzleHarperDBKinetica
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon SimpleDBDatabricksDrizzleHarperDBKinetica
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