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DBMS > Apache Pinot vs. CrateDB vs. etcd vs. IBM Cloudant

System Properties Comparison Apache Pinot vs. CrateDB vs. etcd vs. IBM Cloudant

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonCrateDB  Xexclude from comparisonetcd  Xexclude from comparisonIBM Cloudant  Xexclude from comparison
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyDistributed Database based on LuceneA distributed reliable key-value storeDatabase as a Service offering based on Apache CouchDB
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeDocument store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.38
Rank#275  Overall
#126  Relational DBMS
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
Score2.75
Rank#104  Overall
#19  Document stores
Websitepinot.apache.orgcratedb.cometcd.io
github.com/­etcd-io/­etcd
www.ibm.com/­products/­cloudant
Technical documentationdocs.pinot.apache.orgcratedb.com/­docsetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.ibm.com/­docs/­Cloudant
DeveloperApache Software Foundation and contributorsCrateIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014
Initial release201520132010
Current release1.0.0, September 20233.4, August 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
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 languageJavaJavaGoErlang
Server operating systemsAll OS with a Java JDK11 or higherAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportFreeBSD
Linux
Windows infoexperimental
hosted
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnono
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.nonono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL-like query languageyes, but no triggers and constraints, and PostgreSQL compatibilitynono
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
gRPC
JSON over HTTP
RESTful HTTP/JSON API
Supported programming languagesGo
Java
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
C#
Java
JavaScript
Objective-C
PHP
Ruby
Server-side scripts infoStored proceduresuser defined functions (Javascript)noView functions (Map-Reduce) in JavaScript
Triggersnoyes, watching key changesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategynono infoatomic operations within a document possible
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoOptimistic locking
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
User concepts infoAccess controlrights management via user accountsnoAccess rights for users can be defined per database
More information provided by the system vendor
Apache PinotCrateDBetcdIBM Cloudant
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache PinotCrateDBetcdIBM Cloudant
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