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DBMS > Apache IoTDB vs. Axibase vs. Badger vs. Elasticsearch vs. Google Cloud Bigtable

System Properties Comparison Apache IoTDB vs. Axibase vs. Badger vs. Elasticsearch vs. Google Cloud Bigtable

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonAxibase  Xexclude from comparisonBadger  Xexclude from comparisonElasticsearch  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparison
DescriptionAn IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and FlinkScalable TimeSeries DBMS based on HBase with integrated rule engine and visualizationAn embeddable, persistent, simple and fast Key-Value Store, written purely in Go.A distributed, RESTful modern search and analytics engine based on Apache Lucene infoElasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metricGoogle'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 modelTime Series DBMSTime Series DBMSKey-value storeSearch engineKey-value store
Wide column store
Secondary database modelsDocument store
Spatial DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score0.29
Rank#292  Overall
#25  Time Series DBMS
Score0.14
Rank#331  Overall
#49  Key-value stores
Score135.35
Rank#7  Overall
#1  Search engines
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Websiteiotdb.apache.orgaxibase.com/­docs/­atsd/­financegithub.com/­dgraph-io/­badgerwww.elastic.co/­elasticsearchcloud.google.com/­bigtable
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlgodoc.org/­github.com/­dgraph-io/­badgerwww.elastic.co/­guide/­en/­elasticsearch/­reference/­current/­index.htmlcloud.google.com/­bigtable/­docs
DeveloperApache Software FoundationAxibase CorporationDGraph LabsElasticGoogle
Initial release20182013201720102015
Current release1.1.0, April 2023155858.6, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infoCommunity Edition (single node) is free, Enterprise Edition (distributed) is paidOpen Source infoApache 2.0Open Source infoElastic Licensecommercial
Cloud-based only infoOnly available as a cloud servicenonononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaGoJava
Server operating systemsAll OS with a Java VM (>= 1.8)LinuxBSD
Linux
OS X
Solaris
Windows
All OS with a Java VMhosted
Data schemeyesyesschema-freeschema-free infoFlexible type definitions. Once a type is defined, it is persistentschema-free
Typing infopredefined data types such as float or dateyesyes infoshort, integer, long, float, double, decimal, stringnoyesno
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.nonononono
Secondary indexesyesnonoyes infoAll search fields are automatically indexedno
SQL infoSupport of SQLSQL-like query languageSQL-like query languagenoSQL-like query languageno
APIs and other access methodsJDBC
Native API
JDBC
Proprietary protocol (Network API)
RESTful HTTP API
Java API
RESTful HTTP/JSON API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
Go
Java
PHP
Python
R
Ruby
Go.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesyesnoyesno
Triggersyesyesnoyes infoby using the 'percolation' featureno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)ShardingnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationnoneyesInternal replication in Colossus, and regional replication between two clusters in different zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and SparkyesnoES-Hadoop Connectoryes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
noneEventual Consistency infoSynchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, allImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonononoAtomic single-row operations
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.yesnoMemcached and Redis integrationno
User concepts infoAccess controlyesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Apache IoTDBAxibaseBadgerElasticsearchGoogle Cloud Bigtable
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