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DBMS > CrateDB vs. etcd vs. Qdrant vs. Sphinx

System Properties Comparison CrateDB vs. etcd vs. Qdrant vs. Sphinx

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonetcd  Xexclude from comparisonQdrant  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionDistributed Database based on LuceneA distributed reliable key-value storeA high-performance vector database with neural network or semantic-based matchingOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeVector DBMSSearch engine
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score1.16
Rank#175  Overall
#6  Vector DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitecratedb.cometcd.io
github.com/­etcd-io/­etcd
github.com/­qdrant/­qdrant
qdrant.tech
sphinxsearch.com
Technical documentationcratedb.com/­docsetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
qdrant.tech/­documentationsphinxsearch.com/­docs
DeveloperCrateQdrantSphinx Technologies Inc.
Initial release201320212001
Current release3.4, August 20193.5.1, February 2023
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenononono
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 languageJavaGoRustC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportFreeBSD
Linux
Windows infoexperimental
Docker
Linux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesnoNumbers, Strings, Geo, Booleanno
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 infoKeywords, numberic ranges, geo, full-textyes infofull-text index on all search fields
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynonoSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
gRPC
JSON over HTTP
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Proprietary protocol
Supported programming languages.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
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions (Javascript)nono
Triggersnoyes, watching key changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
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.Collection-level replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistency, tunable 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
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlrights management via user accountsnoKey-based authenticationno
More information provided by the system vendor
CrateDBetcdQdrantSphinx
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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