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DBMS > Amazon CloudSearch vs. LeanXcale vs. SurrealDB vs. Transwarp Hippo

System Properties Comparison Amazon CloudSearch vs. LeanXcale vs. SurrealDB vs. Transwarp Hippo

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Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonLeanXcale  Xexclude from comparisonSurrealDB  Xexclude from comparisonTranswarp Hippo  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons cloudA highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilitiesA fully ACID transactional, developer-friendly, multi-model DBMSCloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets
Primary database modelSearch engineKey-value store
Relational DBMS
Document store
Graph DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.81
Rank#137  Overall
#12  Search engines
Score0.36
Rank#280  Overall
#40  Key-value stores
#129  Relational DBMS
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Score0.05
Rank#386  Overall
#15  Vector DBMS
Websiteaws.amazon.com/­cloudsearchwww.leanxcale.comsurrealdb.comwww.transwarp.cn/­en/­subproduct/­hippo
Technical documentationdocs.aws.amazon.com/­cloudsearchsurrealdb.com/­docs
DeveloperAmazonLeanXcaleSurrealDB Ltd
Initial release2012201520222023
Current releasev1.5.0, May 20241.0, May 2023
License infoCommercial or Open SourcecommercialcommercialOpen Sourcecommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustC++
Server operating systemshostedLinux
macOS
Windows
Linux
macOS
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesVector, Numeric and String
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 search fields are automatically indexedno
SQL infoSupport of SQLnoyes infothrough Apache DerbySQL-like query languageno
APIs and other access methodsHTTP APIJDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector
GraphQL
RESTful HTTP API
WebSocket
RESTful HTTP API
Supported programming languagesC
Java
Scala
Deno
Go
JavaScript (Node.js)
Rust
C++
Java
Python
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWS
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.yesyes
User concepts infoAccess controlauthentication via encrypted signaturesyes, based on authentication and database rulesRole based access control and fine grained access rights

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More resources
Amazon CloudSearchLeanXcaleSurrealDBTranswarp Hippo
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Recent citations in the news

Amazon CloudSearch – Start Searching in One Hour for Less Than $100 / Month | Amazon Web Services
12 April 2012, AWS Blog

Searching CloudTrail Logs Easily with Amazon CloudSearch | AWS Startups Blog
21 October 2014, AWS Blog

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2 June 2020, TechTarget

CloudSearch Update – Price Reduction, Hebrew & Japanese Support, Partitioning, CloudTrail | Amazon Web Services
19 November 2014, AWS Blog

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16 July 2021, Towards Data Science

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