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DBMS > Google Cloud Datastore vs. Manticore Search vs. Qdrant vs. Teradata Aster

System Properties Comparison Google Cloud Datastore vs. Manticore Search vs. Qdrant vs. Teradata Aster

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Editorial information provided by DB-Engines
NameGoogle Cloud Datastore  Xexclude from comparisonManticore Search  Xexclude from comparisonQdrant  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.
DescriptionAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-storage database for search, including full-text search.A high-performance vector database with neural network or semantic-based matchingPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument storeSearch engineVector DBMSRelational DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.13
Rank#71  Overall
#12  Document stores
Score0.23
Rank#301  Overall
#21  Search engines
Score1.53
Rank#145  Overall
#7  Vector DBMS
Websitecloud.google.com/­datastoremanticoresearch.comgithub.com/­qdrant/­qdrant
qdrant.tech
Technical documentationcloud.google.com/­datastore/­docsmanual.manticoresearch.comqdrant.tech/­documentation
DeveloperGoogleManticore SoftwareQdrantTeradata
Initial release2008201720212005
Current release6.0, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2Open Source infoApache Version 2.0commercial
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 languageC++Rust
Server operating systemshostedFreeBSD
Linux
macOS
Windows
Docker
Linux
macOS
Windows
Linux
Data schemeschema-freeFixed schemaschema-freeFlexible 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 dateyes, details hereInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, BooleanNumbers, Strings, Geo, Booleanyes
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.noCan index from XMLnoyes infoin Aster File Store
Secondary indexesyesyes infofull-text index on all search fieldsyes infoKeywords, numberic ranges, geo, full-textyes
SQL infoSupport of SQLSQL-like query language (GQL)SQL-like query languagenoyes
APIs and other access methodsgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresusing Google App Engineuser defined functionsR packages
TriggersCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosSynchronous replication based on Galera libraryCollection-level replicationyes 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 methodsyes infousing Google Cloud Dataflownonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Eventual Consistency, tunable consistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyes infoisolated transactions for atomic changes and binary logging for safe writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Manticore index.yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noKey-based authenticationfine grained access rights according to SQL-standard

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More resources
Google Cloud DatastoreManticore SearchQdrantTeradata Aster
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