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DBMS > Amazon DynamoDB vs. Spark SQL vs. Splice Machine vs. Warp 10

System Properties Comparison Amazon DynamoDB vs. Spark SQL vs. Splice Machine vs. Warp 10

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkTimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.45
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websiteaws.amazon.com/­dynamodbspark.apache.org/­sqlsplicemachine.comwww.warp10.io
Technical documentationdocs.aws.amazon.com/­dynamodbspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-workswww.warp10.io/­content/­02_Getting_started
DeveloperAmazonApache Software FoundationSplice MachineSenX
Initial release2012201420142015
Current release3.5.0 ( 2.13), September 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availableOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaJavaJava
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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.nono
Secondary indexesyesnoyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsyesno
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
JDBC
Native Spark Datasource
ODBC
HTTP API
Jupyter
WebSocket
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infoJavayes infoWarpScript
Triggersyes infoby integration with AWS Lambdanoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar PartitioningSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneMulti-source replication
Source-replica replication
selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)Yes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionnoACIDno
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.noyesyes
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-standardMandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Amazon DynamoDBSpark SQLSplice MachineWarp 10
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