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DBMS > CrateDB vs. Drizzle vs. Qdrant vs. TigerGraph

System Properties Comparison CrateDB vs. Drizzle vs. Qdrant vs. TigerGraph

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonDrizzle  Xexclude from comparisonQdrant  Xexclude from comparisonTigerGraph  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionDistributed Database based on LuceneMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.A high-performance vector database with neural network or semantic-based matchingA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSVector DBMSGraph DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score1.28
Rank#167  Overall
#6  Vector DBMS
Score1.80
Rank#138  Overall
#13  Graph DBMS
Websitecratedb.comgithub.com/­qdrant/­qdrant
qdrant.tech
www.tigergraph.com
Technical documentationcratedb.com/­docsqdrant.tech/­documentationdocs.tigergraph.com
DeveloperCrateDrizzle project, originally started by Brian AkerQdrant
Initial release2013200820212017
Current release7.2.4, September 2012
License infoCommercial or Open SourceOpen SourceOpen Source infoGNU GPLOpen Source infoApache Version 2.0commercial
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 languageJavaC++RustC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportFreeBSD
Linux
OS X
Docker
Linux
macOS
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes
Typing infopredefined data types such as float or dateyesyesNumbers, Strings, Geo, Booleanyes
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 indexesyesyesyes infoKeywords, numberic ranges, geo, full-text
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyes infowith proprietary extensionsnoSQL-like query language (GSQL)
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBCgRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API
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
C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
C++
Java
Server-side scripts infoStored proceduresuser defined functions (Javascript)noyes
Triggersnono infohooks for callbacks inside the server can be used.no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelMulti-source replication
Source-replica replication
Collection-level replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual Consistency, tunable consistency
Foreign keys infoReferential integritynoyesyes infoRelationships in graphs
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 strategyACIDACID
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.noyesno
User concepts infoAccess controlrights management via user accountsPluggable authentication mechanisms infoe.g. LDAP, HTTPKey-based authenticationRole-based access control
More information provided by the system vendor
CrateDBDrizzleQdrantTigerGraph
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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CrateDBDrizzleQdrantTigerGraph
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