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DBMS > Apache IoTDB vs. CockroachDB vs. Dgraph vs. Google Cloud Bigtable vs. HarperDB

System Properties Comparison Apache IoTDB vs. CockroachDB vs. Dgraph vs. Google Cloud Bigtable vs. HarperDB

Editorial information provided by DB-Engines
NameApache IoTDB  Xexclude from comparisonCockroachDB  Xexclude from comparisonDgraph  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  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 FlinkCockroachDB 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.Distributed and scalable native Graph DBMSGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.
Primary database modelTime Series DBMSRelational DBMSGraph DBMSKey-value store
Wide column store
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.18
Rank#173  Overall
#15  Time Series DBMS
Score6.15
Rank#55  Overall
#33  Relational DBMS
Score1.45
Rank#156  Overall
#15  Graph DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.55
Rank#248  Overall
#38  Document stores
Websiteiotdb.apache.orgwww.cockroachlabs.comdgraph.iocloud.google.com/­bigtablewww.harperdb.io
Technical documentationiotdb.apache.org/­UserGuide/­Master/­QuickStart/­QuickStart.htmlwww.cockroachlabs.com/­docsdgraph.io/­docscloud.google.com/­bigtable/­docsdocs.harperdb.io/­docs
DeveloperApache Software FoundationCockroach LabsDgraph Labs, Inc.GoogleHarperDB
Initial release20182015201620152017
Current release1.1.0, April 202323.1.1, May 20233.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0, commercial license availableOpen Source infoApache 2.0commercialcommercial infofree community edition available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoGoNode.js
Server operating systemsAll OS with a Java VM (>= 1.8)Linux
macOS
Windows
Linux
OS X
Windows
hostedLinux
OS X
Data schemeyesdynamic schemaschema-freeschema-freedynamic schema
Typing infopredefined data types such as float or dateyesyesyesnoyes infoJSON 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.nonononono
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like query languageyes, wire compatible with PostgreSQLnonoSQL-like data manipulation statements
APIs and other access methodsJDBC
Native API
JDBCGraphQL query language
gRPC (using protocol buffers) API
HTTP API
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Supported programming languagesC
C#
C++
Go
Java
Python
Scala
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift
Server-side scripts infoStored proceduresyesnononoCustom Functions infosince release 3.1
Triggersyesnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by time range) + vertical partitioning (by deviceId)horizontal 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 RAFTyesShardingA table resides as a whole on one (or more) nodes in a cluster
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicasMulti-source replication using RAFTSynchronous replication via RaftInternal replication in Colossus, and regional replication between two clusters in different zonesyes infothe nodes on which a table resides can be defined
MapReduce infoOffers an API for user-defined Map/Reduce methodsIntegration with Hadoop and Sparknonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Strong Consistency with Raft
Immediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDAtomic single-row operationsAtomic execution of specific operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, using LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlyesRole-based access controlno infoPlanned for future releasesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles

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More resources
Apache IoTDBCockroachDBDgraphGoogle Cloud BigtableHarperDB
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