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DBMS > Apache IoTDB vs. DolphinDB vs. Google Cloud Datastore vs. Splice Machine

System Properties Comparison Apache IoTDB vs. DolphinDB vs. Google Cloud Datastore vs. Splice Machine

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Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonDolphinDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonSplice Machine  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 FlinkDolphinDB 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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSTime Series DBMSDocument storeRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.31
Rank#164  Overall
#14  Time Series DBMS
Score4.03
Rank#78  Overall
#6  Time Series DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteiotdb.apache.orgwww.dolphindb.comcloud.google.com/­datastoresplicemachine.com
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmldocs.dolphindb.cn/­en/­help200/­index.htmlcloud.google.com/­datastore/­docssplicemachine.com/­how-it-works
DeveloperApache Software FoundationDolphinDB, IncGoogleSplice Machine
Initial release2018201820082014
Current release1.1.0, April 2023v2.00.4, January 20223.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community version availablecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query languageSQL-like query languageSQL-like query language (GQL)yes
APIs and other access methodsJDBC
Native API
JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyesyesusing Google App Engineyes infoJava
TriggersyesnoCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal partitioningShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasyesMulti-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparkyesyes infousing Google Cloud DataflowYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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.yesyesnoyes
User concepts infoAccess controlyesAdministrators, Users, GroupsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users, groups and roles according to SQL-standard

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More resources
Apache IoTDBDolphinDBGoogle Cloud DatastoreSplice Machine
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