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DBMS > Amazon DocumentDB vs. Lovefield vs. Splice Machine vs. Teradata Aster

System Properties Comparison Amazon DocumentDB vs. Lovefield vs. Splice Machine vs. Teradata Aster

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonLovefield  Xexclude from comparisonSplice Machine  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceEmbeddable relational database for web apps written in pure JavaScriptOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument storeRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score0.33
Rank#286  Overall
#131  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­documentdbgoogle.github.io/­lovefieldsplicemachine.com
Technical documentationaws.amazon.com/­documentdb/­resourcesgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdsplicemachine.com/­how-it-works
DeveloperGoogleSplice MachineTeradata
Initial release2019201420142005
Current release2.1.12, February 20173.1, March 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScriptJava
Server operating systemshostedserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafariLinux
OS X
Solaris
Windows
Linux
Data schemeschema-freeyesyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
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.nonoyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnoSQL-like query language infovia JavaScript builder patternyesyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
Native Spark Datasource
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
JavaScriptC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnonoyes infoJavaR packages
TriggersnoUsing read-only observersyesno
Partitioning methods infoMethods for storing different data on different nodesnonenoneShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasnoneMulti-source replication
Source-replica replication
yes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noYes, via Full Spark Integrationyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infousing MemoryDByesno
User concepts infoAccess controlAccess rights for users and rolesnoAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBLovefieldSplice MachineTeradata Aster
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