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DBMS > Apache Kylin vs. Google Cloud Datastore vs. Teradata vs. TypeDB

System Properties Comparison Apache Kylin vs. Google Cloud Datastore vs. Teradata vs. TypeDB

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTeradata  Xexclude from comparisonTypeDB infoformerly named Grakn  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA hybrid cloud data analytics software platform (Teradata Vantage)TypeDB provides developers with an expressive, customizable type system to manage their data using an award-winning query language, TypeQL, while building on a high-performance, distributed architecture.
Primary database modelRelational DBMSDocument storeRelational DBMSGraph DBMS infoThe type-theoretic data model of TypeDB subsumes the graph database model.
Object oriented DBMS infoThe data model of TypeDB comprises object-oriented features such as class inheritance and interfaces.
Relational DBMS infoThe type-theoretic data model of TypeDB subsumes the relational database model.
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score44.87
Rank#22  Overall
#15  Relational DBMS
Score0.70
Rank#230  Overall
#20  Graph DBMS
#8  Object oriented DBMS
#106  Relational DBMS
Websitekylin.apache.orgcloud.google.com/­datastorewww.teradata.comtypedb.com
Technical documentationkylin.apache.org/­docscloud.google.com/­datastore/­docsdocs.teradata.comtypedb.com/­docs
DeveloperApache Software Foundation, originally contributed from eBay IncGoogleTeradataVaticle
Initial release2015200819842016
Current release3.1.0, July 2020Teradata Vantage 1.0 MU2, January 20192.28.3, June 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoGPL Version 3, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsLinuxhostedhosted
Linux
Linux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesyes
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.nonoyesno
Secondary indexesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyes
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)SQL-like query language (GQL)yes infoSQL 2016 + extensionsno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
gRPC protocol
TypeDB Console (shell)
TypeDB Studio (IDE)
Supported programming languages.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
All JVM based languages
C
C++
Java
JavaScript (Node.js)
Python
Rust
Server-side scripts infoStored proceduresusing Google App Engineyes infoUDFs, stored procedures, table functions in parallelno
TriggersCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoHashingno
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using PaxosMulti-source replication
Source-replica replication
Synchronous replication via raft
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infousing Google Cloud Dataflownono
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsyesno infosubstituted by the relationship feature
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
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.nonoyesno
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardyes infoat REST API level; other APIs in progress
More information provided by the system vendor
Apache KylinGoogle Cloud DatastoreTeradataTypeDB infoformerly named Grakn
Specific characteristicsTypeDB is a polymorphic database with a conceptual data model, a strong subtyping...
» more
Competitive advantagesTypeDB provides a new level of expressivity, extensibility, interoperability, and...
» more
Typical application scenariosLife sciences : TypeDB makes working with biological data much easier and accelerates...
» more
Licensing and pricing modelsApache f or language drivers, and AGPL and Commercial for the database server. The...
» more

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More resources
Apache KylinGoogle Cloud DatastoreTeradataTypeDB infoformerly named Grakn
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