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

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

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Editorial information provided by DB-Engines
NameDuckDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonManticore Search  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.
DescriptionAn embeddable, in-process, column-oriented SQL OLAP RDBMSAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-storage database for search, including full-text search.Platform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMSDocument storeSearch engineRelational DBMS
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.63
Rank#69  Overall
#37  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.29
Rank#302  Overall
#21  Search engines
Websiteduckdb.orgcloud.google.com/­datastoremanticoresearch.com
Technical documentationduckdb.org/­docscloud.google.com/­datastore/­docsmanual.manticoresearch.com
DeveloperGoogleManticore SoftwareTeradata
Initial release2018200820172005
Current release1.0.0, June 20246.0, February 2023
License infoCommercial or Open SourceOpen Source infoMIT LicensecommercialOpen Source infoGPL version 2commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++
Server operating systemsserver-lesshostedFreeBSD
Linux
macOS
Windows
Linux
Data schemeyesschema-freeFixed schemaFlexible 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 dateyesyes, details hereInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, 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.nonoCan index from XMLyes infoin Aster File Store
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like query languageyes
APIs and other access methodsArrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesC
C# info3rd party driver
C++
Crystal info3rd party driver
Go info3rd party driver
Java
Lisp info3rd party driver
Python
R
Ruby info3rd party driver
Rust
Swift
Zig info3rd party driver
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnousing Google App Engineuser defined functionsR packages
TriggersnoCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication using PaxosSynchronous replication based on Galera libraryyes 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 methodsnoyes infousing Google Cloud Dataflownoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID 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 datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)nofine grained access rights according to SQL-standard

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More resources
DuckDBGoogle Cloud DatastoreManticore SearchTeradata Aster
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