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DBMS > Apache Druid vs. EXASOL vs. Google Cloud Spanner vs. SQream DB vs. Teradata Aster

System Properties Comparison Apache Druid vs. EXASOL vs. Google Cloud Spanner vs. SQream DB vs. Teradata Aster

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonEXASOL  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSQream DB  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.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A 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 GPU-based, columnar RDBMS for big data analytics workloadsPlatform for big data analytics on multistructured data sources and types
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSRelational DBMSRelational DBMSRelational DBMS
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
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websitedruid.apache.orgwww.exasol.comcloud.google.com/­spannersqream.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.exasol.com/­resourcescloud.google.com/­spanner/­docsdocs.sqream.com
DeveloperApache Software Foundation and contributorsExasolGoogleSQream TechnologiesTeradata
Initial release20122000201720172005
Current release29.0.1, April 20242022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++, CUDA, Haskell, Java, Scala
Server operating systemsLinux
OS X
Unix
hostedLinuxLinux
Data schemeyes infoschema-less columns are supportedyesyesyesFlexible 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, ANSI Standard SQL Typesyes
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 infoin Aster File Store
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL for queryingyesyes infoQuery statements complying to ANSI 2011yesyes
APIs and other access methodsJDBC
RESTful HTTP/JSON API
.Net
JDBC
ODBC
WebSocket
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
.Net
JDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Java
Lua
Python
R
Go
Java
JavaScript (Node.js)
Python
C++
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnouser defined functionsnouser defined functions in PythonR packages
Triggersnoyesnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardinghorizontal and vertical partitioningSharding
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.noneyes 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 infoHadoop integrationyes infousing Google Cloud Dataflownoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoStrict serializable isolationACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
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 according to SQL-standardAccess 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 DruidEXASOLGoogle Cloud SpannerSQream DBTeradata Aster
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