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DBMS > Apache IoTDB vs. Coveo vs. CrateDB vs. etcd

System Properties Comparison Apache IoTDB vs. Coveo vs. CrateDB vs. etcd

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCoveo  Xexclude from comparisonCrateDB  Xexclude from comparisonetcd  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 FlinkAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentDistributed Database based on LuceneA distributed reliable key-value store
Primary database modelTime Series DBMSSearch engineDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score2.11
Rank#118  Overall
#11  Search engines
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Websiteiotdb.apache.orgwww.coveo.comcratedb.cometcd.io
github.com/­etcd-io/­etcd
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.coveo.comcratedb.com/­docsetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
DeveloperApache Software FoundationCoveoCrate
Initial release201820122013
Current release1.1.0, April 20233.4, August 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen SourceOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaJavaGo
Server operating systemsAll OS with a Java VM (>= 1.8)hostedAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportFreeBSD
Linux
Windows infoexperimental
Data schemeyeshybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationFlexible Schema (defined schema, partial schema, schema free)schema-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 indexesyesyesyesno
SQL infoSupport of SQLSQL-like query languagenoyes, but no triggers and constraints, and PostgreSQL compatibilityno
APIs and other access methodsJDBC
Native API
RESTful HTTP APIADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
gRPC
JSON over HTTP
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
Java
JavaScript
Python
.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Server-side scripts infoStored proceduresyesnouser defined functions (Javascript)no
Triggersyesyesnoyes, watching key changes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)yesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesConfigurable replication on table/partition-levelUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesno infounique row identifiers can be used for implementing an optimistic concurrency control strategyno
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.yesnono
User concepts infoAccess controlyesgranular access controls, API key management, content filtersrights management via user accountsno
More information provided by the system vendor
Apache IoTDBCoveoCrateDBetcd
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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Apache IoTDBCoveoCrateDBetcd
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