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DBMS > ArcadeDB vs. EsgynDB vs. Google Cloud Bigtable vs. HarperDB

System Properties Comparison ArcadeDB vs. EsgynDB vs. Google Cloud Bigtable vs. HarperDB

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Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparison
DescriptionFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionGoogle'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 modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Relational DBMSKey-value store
Wide column store
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.02
Rank#366  Overall
#50  Document stores
#38  Graph DBMS
#53  Key-value stores
#36  Time Series DBMS
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.55
Rank#248  Overall
#38  Document stores
Websitearcadedb.comwww.esgyn.cncloud.google.com/­bigtablewww.harperdb.io
Technical documentationdocs.arcadedb.comcloud.google.com/­bigtable/­docsdocs.harperdb.io/­docs
DeveloperArcade DataEsgynGoogleHarperDB
Initial release2021201520152017
Current releaseSeptember 20213.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infofree community edition available
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaNode.js
Server operating systemsAll OS with a Java VMLinuxhostedLinux
OS X
Data schemeschema-freeyesschema-freedynamic schema
Typing infopredefined data types such as float or dateyesyesnoyes 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.nononono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-like query language, no joinsyesnoSQL-like data manipulation statements
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
Supported programming languagesJavaAll languages supporting JDBC/ODBC/ADO.NetC#
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 proceduresJava Stored ProceduresnoCustom Functions infosince release 3.1
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingA table resides as a whole on one (or more) nodes in a cluster
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication between multi datacentersInternal 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 methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityyes inforelationship in graphsyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDAtomic single-row operationsAtomic execution of specific operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes, using LMDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess 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
ArcadeDBEsgynDBGoogle Cloud BigtableHarperDB
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