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DBMS > Apache Druid vs. Google Cloud Spanner vs. InterSystems Caché vs. Teradata Aster

System Properties Comparison Apache Druid vs. Google Cloud Spanner vs. InterSystems Caché vs. Teradata Aster

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.A multi-model DBMS and application serverPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSKey-value store
Object oriented DBMS
Relational DBMS
Relational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Websitedruid.apache.orgcloud.google.com/­spannerwww.intersystems.com/­products/­cache
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­spanner/­docsdocs.intersystems.com
DeveloperApache Software Foundation and contributorsGoogleInterSystemsTeradata
Initial release2012201719972005
Current release29.0.1, April 20242018.1.4, May 2020
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemsLinux
OS X
Unix
hostedAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
Data schemeyes infoschema-less columns are supportedyesdepending on used data modelFlexible 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 dateyesyesyesyes
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.nonoyesyes infoin Aster File Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingyes infoQuery statements complying to ANSI 2011yesyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
.NET Client API
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
C#
C++
Java
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnonoyesR packages
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication with 3 replicas for regional instances.Source-replica 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 methodsnoyes infousing Google Cloud Dataflownoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationACIDACID
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 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)Access rights for users, groups and rolesfine grained access rights according to SQL-standard

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More resources
Apache DruidGoogle Cloud SpannerInterSystems CachéTeradata Aster
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