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DBMS > AnzoGraph DB vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. HarperDB

System Properties Comparison AnzoGraph DB vs. Dgraph vs. EsgynDB vs. Google Cloud Bigtable vs. HarperDB

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonDgraph  Xexclude from comparisonEsgynDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonHarperDB  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationDistributed and scalable native Graph DBMSEnterprise-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 modelGraph DBMS
RDF store
Graph DBMSRelational DBMSKey-value store
Wide column store
Document store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.27
Rank#302  Overall
#24  Graph DBMS
#13  RDF stores
Score1.48
Rank#158  Overall
#15  Graph DBMS
Score0.23
Rank#319  Overall
#141  Relational DBMS
Score3.58
Rank#92  Overall
#14  Key-value stores
#8  Wide column stores
Score0.55
Rank#252  Overall
#38  Document stores
Websitecambridgesemantics.com/­anzographdgraph.iowww.esgyn.cncloud.google.com/­bigtablewww.harperdb.io
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmdgraph.io/­docscloud.google.com/­bigtable/­docsdocs.harperdb.io/­docs
DeveloperCambridge SemanticsDgraph Labs, Inc.EsgynGoogleHarperDB
Initial release20182016201520152017
Current release2.3, January 20213.1, August 2021
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache 2.0commercialcommercialcommercial infofree community edition available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageGoC++, JavaNode.js
Server operating systemsLinuxLinux
OS X
Windows
LinuxhostedLinux
OS X
Data schemeSchema-free and OWL/RDFS-schema supportschema-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.nonononono
Secondary indexesnoyesyesnoyes
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.noyesnoSQL-like data manipulation statements
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
GraphQL query language
gRPC (using protocol buffers) API
HTTP API
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 languagesC++
Java
Python
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
All 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 proceduresuser defined functions and aggregatesnoJava Stored ProceduresnoCustom Functions infosince release 3.1
Triggersnonononono
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingyesShardingShardingA table resides as a whole on one (or more) nodes in a cluster
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterSynchronous replication via RaftMulti-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 methodsKerberos/HDFS data loadingnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic 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 controlAccess rights for users and rolesno infoPlanned for future releasesfine 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
AnzoGraph DBDgraphEsgynDBGoogle Cloud BigtableHarperDB
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