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DBMS > Apache Druid vs. Google Cloud Datastore vs. SurrealDB vs. Teradata

System Properties Comparison Apache Druid vs. Google Cloud Datastore vs. SurrealDB vs. Teradata

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSurrealDB  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA fully ACID transactional, developer-friendly, multi-model DBMSA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelRelational DBMS
Time Series DBMS
Document storeDocument store
Graph DBMS
Relational 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
Score3.25
Rank#90  Overall
#47  Relational DBMS
#7  Time Series DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score1.02
Rank#190  Overall
#33  Document stores
#18  Graph DBMS
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitedruid.apache.orgcloud.google.com/­datastoresurrealdb.comwww.teradata.com
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­datastore/­docssurrealdb.com/­docsdocs.teradata.com
DeveloperApache Software Foundation and contributorsGoogleSurrealDB LtdTeradata
Initial release2012200820221984
Current release29.0.1, April 2024v1.5.0, May 2024Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Sourcecommercial
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 languageJavaRust
Server operating systemsLinux
OS X
Unix
hostedLinux
macOS
Windows
hosted
Linux
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeyes
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.nonoyes
Secondary indexesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLSQL for queryingSQL-like query language (GQL)SQL-like query languageyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
GraphQL
RESTful HTTP API
WebSocket
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Deno
Go
JavaScript (Node.js)
Rust
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 nodesSharding infomanual/auto, time-basedShardingSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes 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 Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID 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.nonoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes, based on authentication and database rulesfine grained access rights according to SQL-standard

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More resources
Apache DruidGoogle Cloud DatastoreSurrealDBTeradata
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