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

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

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Editorial information provided by DB-Engines
NameApache Kylin  Xexclude from comparisonCockroachDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMS
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
Score5.73
Rank#58  Overall
#34  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitekylin.apache.orgwww.cockroachlabs.comcloud.google.com/­datastorewww.teradata.com
Technical documentationkylin.apache.org/­docswww.cockroachlabs.com/­docscloud.google.com/­datastore/­docsdocs.teradata.com
DeveloperApache Software Foundation, originally contributed from eBay IncCockroach LabsGoogleTeradata
Initial release2015201520081984
Current release3.1.0, July 202024.1.0, May 2024Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0, commercial license availablecommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGo
Server operating systemsLinuxLinux
macOS
Windows
hostedhosted
Linux
Data schemeyesdynamic schemaschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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.nononoyes
Secondary indexesyesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLANSI SQL for queries (using Apache Calcite)yes, wire compatible with PostgreSQLSQL-like query language (GQL)yes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresnousing Google App Engineyes infoUDFs, stored procedures, table functions in parallel
TriggersnoCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTMulti-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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
Foreign keys infoReferential integrityyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
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.nononoyes
User concepts infoAccess controlRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Apache KylinCockroachDBGoogle Cloud DatastoreTeradata
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