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DBMS > Datomic vs. Google Cloud Bigtable vs. Hazelcast vs. InfluxDB

System Properties Comparison Datomic vs. Google Cloud Bigtable vs. Hazelcast vs. InfluxDB

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHazelcast  Xexclude from comparisonInfluxDB  Xexclude from comparison
DescriptionDatomic 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.A widely adopted in-memory data gridDBMS for storing time series, events and metrics
Primary database modelRelational DBMSKey-value store
Wide column store
Key-value storeTime Series DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.55
Rank#144  Overall
#67  Relational DBMS
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score5.72
Rank#59  Overall
#6  Key-value stores
Score22.12
Rank#28  Overall
#1  Time Series DBMS
Websitewww.datomic.comcloud.google.com/­bigtablehazelcast.comwww.influxdata.com/­products/­influxdb-overview
Technical documentationdocs.datomic.comcloud.google.com/­bigtable/­docshazelcast.org/­imdg/­docsdocs.influxdata.com/­influxdb
DeveloperCognitectGoogleHazelcast
Initial release2012201520082013
Current release1.0.7180, July 20245.3.6, November 20232.7.6, April 2024
License infoCommercial or Open Sourcecommercial infolimited edition freecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoMIT-License; commercial enterprise version available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureJavaGo
Server operating systemsAll OS with a Java VMhostedAll OS with a Java VMLinux
OS X infothrough Homebrew
Data schemeyesschema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesnoyesNumeric data and Strings
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.nonoyes infothe object must implement a serialization strategyno
Secondary indexesyesnoyesno
SQL infoSupport of SQLnonoSQL-like query languageSQL-like query language
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JCache
JPA
Memcached protocol
RESTful HTTP API
HTTP API
JSON over UDP
Supported programming languagesClojure
Java
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes infoEvent Listeners, Executor Servicesno
TriggersBy using transaction functionsnoyes infoEventsno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersShardingShardingSharding infoin enterprise version only
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersInternal replication in Colossus, and regional replication between two clusters in different zonesyes infoReplicated Mapselectable replication factor infoin enterprise version only
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic single-row operationsone or two-phase-commit; repeatable reads; read commitedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyesyes infoDepending on used storage engine
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Role-based access controlsimple rights management via user accounts
More information provided by the system vendor
DatomicGoogle Cloud BigtableHazelcastInfluxDB
Specific characteristicsInfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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