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DBMS > Apache Druid vs. Google Cloud Datastore vs. Hypertable vs. Kinetica vs. Vertica

System Properties Comparison Apache Druid vs. Google Cloud Datastore vs. Hypertable vs. Kinetica vs. Vertica

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonHypertable  Xexclude from comparisonKinetica  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
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 PlatformAn open source BigTable implementation based on distributed file systems such as HadoopFully vectorized database across both GPUs and CPUsCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.
Primary database modelRelational DBMS
Time Series DBMS
Document storeWide column storeRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsSpatial DBMS
Time Series 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
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score10.06
Rank#42  Overall
#26  Relational DBMS
Websitedruid.apache.orgcloud.google.com/­datastorewww.kinetica.comwww.vertica.com
Technical documentationdruid.apache.org/­docs/­latest/­designcloud.google.com/­datastore/­docsdocs.kinetica.comvertica.com/­documentation
DeveloperApache Software Foundation and contributorsGoogleHypertable Inc.KineticaOpenText infopreviously Micro Focus and Hewlett Packard
Initial release20122008200920122005
Current release29.0.1, April 20240.9.8.11, March 20167.1, August 202112.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoGNU version 3. Commercial license availablecommercialcommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenoyesnonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C, C++C++
Server operating systemsLinux
OS X
Unix
hostedLinux
OS X
Windows infoan inofficial Windows port is available
LinuxLinux
Data schemeyes infoschema-less columns are supportedschema-freeschema-freeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyesyes, details herenoyesyes
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 indexesyesyesrestricted infoonly exact value or prefix value scansyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL for queryingSQL-like query language (GQL)noSQL-like DML and DDL statementsFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
C++ API
Thrift
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnousing Google App Enginenouser defined functionsyes, PostgreSQL PL/pgSQL, with minor differences
TriggersnoCallbacks using the Google Apps Enginenoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replication using Paxosselectable replication factor on file system levelSource-replica replicationMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflowyesnono infoBi-directional Spark integration
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 ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnonoACID
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.nonoyes infoGPU vRAM or System RAMno
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)noAccess rights for users and roles on table levelfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash
More information provided by the system vendor
Apache DruidGoogle Cloud DatastoreHypertableKineticaVertica infoOpenText™ Vertica™
Specific characteristicsDeploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantagesFast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
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Typical application scenariosCommunication and network analytics, Embedded analytics, Fraud monitoring and Risk...
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Key customersAbiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
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Licensing and pricing modelsCost-based models and subscription-based models are both available. One license is...
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More resources
Apache DruidGoogle Cloud DatastoreHypertableKineticaVertica infoOpenText™ Vertica™
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