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DBMS > Apache IoTDB vs. Cubrid vs. Google Cloud Spanner vs. Sphinx vs. YDB

System Properties Comparison Apache IoTDB vs. Cubrid vs. Google Cloud Spanner vs. Sphinx vs. YDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCubrid  Xexclude from comparisonGoogle Cloud Spanner  Xexclude from comparisonSphinx  Xexclude from comparisonYDB  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 FlinkCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPA horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.Open source search engine for searching in data from different sources, e.g. relational databasesA distributed fault-tolerant database service, with high availability, scalability, immediate consistency and ACID transactions and providing an Amazon DynamoDB compatible API
Primary database modelTime Series DBMSRelational DBMSRelational DBMSSearch engineDocument store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score2.89
Rank#103  Overall
#52  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.35
Rank#278  Overall
#43  Document stores
#127  Relational DBMS
Websiteiotdb.apache.orgcubrid.com (korean)
cubrid.org (english)
cloud.google.com/­spannersphinxsearch.comgithub.com/­ydb-platform/­ydb
ydb.tech
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlcubrid.org/­manualscloud.google.com/­spanner/­docssphinxsearch.com/­docsydb.tech/­en/­docs
DeveloperApache Software FoundationCUBRID Corporation, CUBRID FoundationGoogleSphinx Technologies Inc.Yandex
Initial release20182008201720012019
Current release1.1.0, April 202311.0, January 20213.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialOpen Source infoGPL version 2, commercial licence availableOpen Source infoApache 2.0; commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++, JavaC++
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
hostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
Data schemeyesyesyesyesFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyesyesnoyes
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 indexesyesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLSQL-like query languageyesyes infoQuery statements complying to ANSI 2011SQL-like query language (SphinxQL)SQL-like query language (YQL)
APIs and other access methodsJDBC
Native API
ADO.NET
JDBC
ODBC
OLE DB
gRPC (using protocol buffers) API
JDBC infoAt present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API
Proprietary protocolRESTful HTTP API (DynamoDB compatible)
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Go
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Go
Java
JavaScript (Node.js)
PHP
Python
Server-side scripts infoStored proceduresyesJava Stored Proceduresnonono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)noneShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasSource-replica replicationMulti-source replication with 3 replicas for regional instances.noneActive-passive shard replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyes infoby using interleaved tables, this features focuses more on performance improvements than on referential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoStrict serializable isolationnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlyesfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights defined for Yandex Cloud users

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More resources
Apache IoTDBCubridGoogle Cloud SpannerSphinxYDB
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