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DBMS > etcd vs. HugeGraph vs. Netezza vs. Spark SQL

System Properties Comparison etcd vs. HugeGraph vs. Netezza vs. Spark SQL

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonHugeGraph  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed reliable key-value storeA fast-speed and highly-scalable Graph DBMSData warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeGraph DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.13
Rank#336  Overall
#32  Graph DBMS
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
github.com/­hugegraph
hugegraph.apache.org
www.ibm.com/­products/­netezzaspark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hugegraph.apache.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperBaiduIBMApache Software Foundation
Initial release201820002014
Current release3.4, August 20190.93.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaScala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
macOS
Unix
Linux infoincluded in applianceLinux
OS X
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or datenoyesyesyes
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 indexesnoyes infoalso supports composite index and range indexyesno
SQL infoSupport of SQLnonoyesSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
Java API
RESTful HTTP API
TinkerPop Gremlin
JDBC
ODBC
OLE DB
JDBC
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Groovy
Java
Python
C
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoasynchronous Gremlin script jobsyesno
Triggersyes, watching key changesnonono
Partitioning methods infoMethods for storing different data on different nodesyes infodepending on used storage backend, e.g. Cassandra and HBaseShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes infodepending on used storage backend, e.g. Cassandra and HBaseSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnovia hugegraph-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes infoedges in graphnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.noyesno
User concepts infoAccess controlnoUsers, roles and permissionsUsers with fine-grained authorization conceptno

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More resources
etcdHugeGraphNetezza infoAlso called PureData System for Analytics by IBMSpark SQL
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