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DBMS > Apache Druid vs. Google Cloud Spanner vs. GridDB vs. InfinityDB

System Properties Comparison Apache Druid vs. Google Cloud Spanner vs. GridDB vs. InfinityDB

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonGridDB  Xexclude from comparisonInfinityDB  Xexclude from comparison
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.Scalable in-memory time series database optimized for IoT and Big DataA Java embedded Key-Value Store which extends the Java Map interface
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSTime Series DBMSKey-value store
Secondary database modelsKey-value store
Relational 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
Score2.84
Rank#100  Overall
#51  Relational DBMS
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.08
Rank#365  Overall
#55  Key-value stores
Websitedruid.apache.orgcloud.google.com/­spannergriddb.netboilerbay.com
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­spanner/­docsdocs.griddb.netboilerbay.com/­infinitydb/­manual
DeveloperApache Software Foundation and contributorsGoogleToshiba CorporationBoiler Bay Inc.
Initial release2012201720132002
Current release29.0.1, April 20245.1, August 20224.0
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemsLinux
OS X
Unix
hostedLinuxAll OS with a Java VM
Data schemeyes infoschema-less columns are supportedyesyesyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgrade
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arrays
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.nononono
Secondary indexesyesyesyesno infomanual creation possible, using inversions based on multi-value capability
SQL infoSupport of SQLSQL for queryingyes infoQuery statements complying to ANSI 2011SQL92, SQL-like TQL (Toshiba Query Language)no
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
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
JavaScript (Node.js)
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Server-side scripts infoStored proceduresnononono
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingnone
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 replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflowConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersImmediate Consistency infoREAD-COMMITTED or SERIALIZED
Foreign keys infoReferential integritynoyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono infomanual creation possible, using inversions based on multi-value capability
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoStrict serializable isolationACID at container levelACID infoOptimistic locking for transactions; no isolation for bulk loads
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 can be defined per databaseno
More information provided by the system vendor
Apache DruidGoogle Cloud SpannerGridDBInfinityDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
Apache DruidGoogle Cloud SpannerGridDBInfinityDB
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