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DBMS > Apache Druid vs. Datomic vs. Google Cloud Bigtable vs. Warp 10

System Properties Comparison Apache Druid vs. Datomic vs. Google Cloud Bigtable vs. Warp 10

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelRelational DBMS
Time Series DBMS
Relational DBMSKey-value store
Wide column store
Time Series 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
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitedruid.apache.orgwww.datomic.comcloud.google.com/­bigtablewww.warp10.io
Technical documentationdruid.apache.org/­docs/­latest/­designdocs.datomic.comcloud.google.com/­bigtable/­docswww.warp10.io/­content/­02_Getting_started
DeveloperApache Software Foundation and contributorsCognitectGoogleSenX
Initial release2012201220152015
Current release29.0.1, April 20241.0.6735, June 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercial infolimited edition freecommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, ClojureJava
Server operating systemsLinux
OS X
Unix
All OS with a Java VMhostedLinux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnoyes
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 queryingnonono
APIs and other access methodsJDBC
RESTful HTTP/JSON API
RESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
HTTP API
Jupyter
WebSocket
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Clojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes infoTransaction Functionsnoyes infoWarpScript
TriggersnoBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basednone infoBut extensive use of caching in the application peersShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesnone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency infobased on HBase
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentnoyes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources
Apache DruidDatomicGoogle Cloud BigtableWarp 10
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