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DBMS > AnzoGraph DB vs. Apache Kylin vs. etcd vs. HBase vs. HEAVY.AI

System Properties Comparison AnzoGraph DB vs. Apache Kylin vs. etcd vs. HBase vs. HEAVY.AI

Editorial information provided by DB-Engines
NameAnzoGraph DB  Xexclude from comparisonApache Kylin  Xexclude from comparisonetcd  Xexclude from comparisonHBase  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparison
DescriptionScalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualizationA distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stackA distributed reliable key-value storeWide-column store based on Apache Hadoop and on concepts of BigTableA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware
Primary database modelGraph DBMS
RDF store
Relational DBMSKey-value storeWide column storeRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.29
Rank#303  Overall
#25  Graph DBMS
#14  RDF stores
Score1.25
Rank#170  Overall
#77  Relational DBMS
Score7.03
Rank#54  Overall
#5  Key-value stores
Score27.97
Rank#26  Overall
#2  Wide column stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Websitecambridgesemantics.com/­anzographkylin.apache.orgetcd.io
github.com/­etcd-io/­etcd
hbase.apache.orggithub.com/­heavyai/­heavydb
www.heavy.ai
Technical documentationdocs.cambridgesemantics.com/­anzograph/­userdoc/­home.htmkylin.apache.org/­docsetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hbase.apache.org/­book.htmldocs.heavy.ai
DeveloperCambridge SemanticsApache Software Foundation, originally contributed from eBay IncApache Software Foundation infoApache top-level project, originally developed by PowersetHEAVY.AI, Inc.
Initial release2018201520082016
Current release2.3, January 20213.1.0, July 20203.4, August 20192.3.4, January 20215.10, January 2022
License infoCommercial or Open Sourcecommercial infofree trial version availableOpen Source infoApache Version 2.0Open Source infoApache Version 2.0Open Source infoApache version 2Open Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaGoJavaC++ and CUDA
Server operating systemsLinuxLinuxFreeBSD
Linux
Windows infoexperimental
Linux
Unix
Windows infousing Cygwin
Linux
Data schemeSchema-free and OWL/RDFS-schema supportyesschema-freeschema-free, schema definition possibleyes
Typing infopredefined data types such as float or dateyesnooptions to bring your own types, AVROyes
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 indexesnoyesnonono
SQL infoSupport of SQLSPARQL and SPARQL* as primary query language. Cypher preview.ANSI SQL for queries (using Apache Calcite)nonoyes
APIs and other access methodsApache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL
JDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
Java API
RESTful HTTP API
Thrift
JDBC
ODBC
Thrift
Vega
Supported programming languagesC++
Java
Python
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C
C#
C++
Groovy
Java
PHP
Python
Scala
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infoCoprocessors in Javano
Triggersnoyes, watching key changesyesno
Partitioning methods infoMethods for storing different data on different nodesAutomatic shardingShardingSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication in MPP-ClusterUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication
Source-replica replication
Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsKerberos/HDFS data loadingyesnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency in MPP-ClusterImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infonot needed in graphsnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)no
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyesyes
User concepts infoAccess controlAccess rights for users and rolesnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standard

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More resources
AnzoGraph DBApache KylinetcdHBaseHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022
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