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DBMS > Apache Druid vs. Coveo vs. Geode vs. Google Cloud Bigtable

System Properties Comparison Apache Druid vs. Coveo vs. Geode vs. Google Cloud Bigtable

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonCoveo  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentGeode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.
Primary database modelRelational DBMS
Time Series DBMS
Search engineKey-value storeKey-value store
Wide column 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
Score2.28
Rank#114  Overall
#11  Search engines
Score1.92
Rank#131  Overall
#23  Key-value stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websitedruid.apache.orgwww.coveo.comgeode.apache.orgcloud.google.com/­bigtable
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.coveo.comgeode.apache.org/­docscloud.google.com/­bigtable/­docs
DeveloperApache Software Foundation and contributorsCoveoOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.Google
Initial release2012201220022015
Current release29.0.1, April 20241.1, February 2017
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache Version 2; commercial licenses available as Gemfirecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemsLinux
OS X
Unix
hostedAll OS with a Java VM infothe JDK (8 or later) is also requiredhosted
Data schemeyes infoschema-less columns are supportedhybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesyesnono
SQL infoSupport of SQLSQL for queryingnoSQL-like query language (OQL)no
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIJava Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
Java
JavaScript
Python
.Net
All JVM based languages
C++
Groovy
Java
Scala
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonouser defined functionsno
Triggersnoyesyes infoCache Event Listenersno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedyesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyesMulti-source replicationInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesyes, on a single nodeAtomic single-row operations
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.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemgranular access controls, API key management, content filtersAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache DruidCoveoGeodeGoogle Cloud Bigtable
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