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

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

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonDrizzle  Xexclude from comparisonGeode  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 ScioreMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesUltra-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 storeRelational DBMSKey-value storeDocument 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
Score1.92
Rank#131  Overall
#23  Key-value stores
Score0.55
Rank#248  Overall
#38  Document stores
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteaws.amazon.com/­simpledbgeode.apache.orgwww.harperdb.iowww.kinetica.com
Technical documentationdocs.aws.amazon.com/­simpledbgeode.apache.org/­docsdocs.harperdb.io/­docsdocs.kinetica.com
DeveloperAmazonDrizzle project, originally started by Brian AkerOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.HarperDBKinetica
Initial release20072008200220172012
Current release7.2.4, September 20121.1, February 20173.1, August 20217.1, August 2021
License infoCommercial or Open SourcecommercialOpen Source infoGNU GPLOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercial infofree community edition availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaNode.jsC, C++
Server operating systemshostedFreeBSD
Linux
OS X
All OS with a Java VM infothe JDK (8 or later) is also requiredLinux
OS X
Linux
Data schemeschema-freeyesschema-freedynamic schemayes
Typing infopredefined data types such as float or datenoyesyesyes 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.nonono
Secondary indexesyes infoAll columns are indexed automaticallyyesnoyesyes
SQL infoSupport of SQLnoyes infowith proprietary extensionsSQL-like query language (OQL)SQL-like data manipulation statementsSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBCJava Client API
Memcached protocol
RESTful HTTP API
JDBC
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
C
C++
Java
PHP
.Net
All JVM based languages
C++
Groovy
Java
Scala
.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 proceduresnonouser defined functionsCustom Functions infosince release 3.1user defined functions
Triggersnono infohooks for callbacks inside the server can be used.yes infoCache Event Listenersnoyes 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 applicationShardingShardingA table resides as a whole on one (or more) nodes in a clusterSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
Multi-source replicationyes infothe nodes on which a table resides can be definedSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDyes, on a single nodeAtomic 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.yesyesyes 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 per client and object definableAccess rights for users and rolesAccess rights for users and roles on table level

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More resources
Amazon SimpleDBDrizzleGeodeHarperDBKinetica
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