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DBMS > Amazon SimpleDB vs. Databricks vs. Google Cloud Spanner vs. Splice Machine vs. XTDB

System Properties Comparison Amazon SimpleDB vs. Databricks vs. Google Cloud Spanner vs. Splice Machine vs. XTDB

Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonDatabricks  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSplice Machine  Xexclude from comparisonXTDB infoformerly named Crux  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 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.A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA general purpose database with bitemporal SQL and Datalog and graph queries
Primary database modelKey-value storeDocument store
Relational DBMS
Relational DBMSRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.88
Rank#133  Overall
#23  Key-value stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Score0.18
Rank#332  Overall
#46  Document stores
Websiteaws.amazon.com/­simpledbwww.databricks.comcloud.google.com/­spannersplicemachine.comgithub.com/­xtdb/­xtdb
www.xtdb.com
Technical documentationdocs.aws.amazon.com/­simpledbdocs.databricks.comcloud.google.com/­spanner/­docssplicemachine.com/­how-it-workswww.xtdb.com/­docs
DeveloperAmazonDatabricksGoogleSplice MachineJuxt Ltd.
Initial release20072013201720142019
Current release3.1, March 20211.19, September 2021
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source infoMIT License
Cloud-based only infoOnly available as a cloud serviceyesyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaClojure
Server operating systemshostedhostedhostedLinux
OS X
Solaris
Windows
All OS with a Java 8 (and higher) VM
Linux
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or datenoyesyesyes, extensible-data-notation format
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 infoQuery statements complying to ANSI 2011yeslimited SQL, making use of Apache Calcite
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
HTTP REST
JDBC
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
Python
R
Scala
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Clojure
Java
Server-side scripts infoStored proceduresnouser defined functions and aggregatesnoyes infoJavano
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingShared Nothhing Auto-Sharding, Columnar Partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesMulti-source replication with 3 replicas for regional instances.Multi-source replication
Source-replica replication
yes, each node contains all data
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflowYes, 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationACIDACID infoStrict serializable isolationACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
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 based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Amazon SimpleDBDatabricksGoogle Cloud SpannerSplice MachineXTDB infoformerly named Crux
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon SimpleDBDatabricksGoogle Cloud SpannerSplice MachineXTDB infoformerly named Crux
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