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DBMS > Amazon SimpleDB vs. Apache Impala vs. Hypertable vs. Splice Machine

System Properties Comparison Amazon SimpleDB vs. Apache Impala vs. Hypertable vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonApache Impala  Xexclude from comparisonHypertable  Xexclude from comparisonSplice Machine  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed 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 ScioreAnalytic DBMS for HadoopAn open source BigTable implementation based on distributed file systems such as HadoopOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeRelational DBMSWide column storeRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#133  Overall
#23  Key-value stores
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­simpledbimpala.apache.orgsplicemachine.com
Technical documentationdocs.aws.amazon.com/­simpledbimpala.apache.org/­impala-docs.htmlsplicemachine.com/­how-it-works
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaHypertable Inc.Splice Machine
Initial release2007201320092014
Current release4.1.0, June 20220.9.8.11, March 20163.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoGNU version 3. Commercial license availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemshostedLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or datenoyesnoyes
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
Secondary indexesyes infoAll columns are indexed automaticallyyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
C++ API
Thrift
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBCC++
Java
Perl
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reducenoyes infoJava
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorselectable replication factor on file system levelMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyesYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual 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 applicationnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.noyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon SimpleDBApache ImpalaHypertableSplice Machine
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