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DBMS > CockroachDB vs. DolphinDB vs. Microsoft Azure Table Storage vs. NSDb vs. TimescaleDB

System Properties Comparison CockroachDB vs. DolphinDB vs. Microsoft Azure Table Storage vs. NSDb vs. TimescaleDB

Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonDolphinDB  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonNSDb  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.A Wide Column Store for rapid development using massive semi-structured datasetsScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSTime Series DBMS
Vector DBMS
Wide column storeTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score4.74
Rank#67  Overall
#36  Relational DBMS
Score2.72
Rank#100  Overall
#8  Time Series DBMS
#5  Vector DBMS
Score3.55
Rank#80  Overall
#6  Wide column stores
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Score4.06
Rank#73  Overall
#5  Time Series DBMS
Websitewww.cockroachlabs.comwww.dolphindb.comazure.microsoft.com/­en-us/­services/­storage/­tablesnsdb.iowww.timescale.com
Technical documentationwww.cockroachlabs.com/­docsdocs.dolphindb.cn/­en/­help200/­index.htmlnsdb.io/­Architecturedocs.timescale.com
DeveloperCockroach LabsDolphinDB, IncMicrosoftTimescale
Initial release20152018201220172017
Current release24.1.0, May 2024v2.00.4, January 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availablecommercial infofree community version availablecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++Java, ScalaC
Server operating systemsLinux
macOS
Windows
Linux
Windows
hostedLinux
macOS
Linux
OS X
Windows
Data schemedynamic schemayesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes: int, bigint, decimal, stringnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonononoyes
Secondary indexesyesyesnoall fields are automatically indexedyes
SQL infoSupport of SQLyes, wire compatible with PostgreSQLSQL-like query languagenoSQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBCJDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
RESTful HTTP APIgRPC
HTTP REST
WebSocket
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyesnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFThorizontal partitioningSharding infoImplicit feature of the cloud serviceShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTyesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesoptimistic lockingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Luceneyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlRole-based access controlAdministrators, Users, GroupsAccess rights based on private key authentication or shared access signaturesfine grained access rights according to SQL-standard

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More resources
CockroachDBDolphinDBMicrosoft Azure Table StorageNSDbTimescaleDB
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