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DBMS > etcd vs. HarperDB vs. HEAVY.AI vs. Sadas Engine vs. Spark SQL

System Properties Comparison etcd vs. HarperDB vs. HEAVY.AI vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonHarperDB  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed reliable key-value storeUltra-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.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value storeDocument storeRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.55
Rank#248  Overall
#38  Document stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.harperdb.iogithub.com/­heavyai/­heavydb
www.heavy.ai
www.sadasengine.comspark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.harperdb.io/­docsdocs.heavy.aiwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperHarperDBHEAVY.AI, Inc.SADAS s.r.l.Apache Software Foundation
Initial release2017201620062014
Current release3.4, August 20193.1, August 20215.10, January 20228.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercial infofree community edition availableOpen Source infoApache Version 2; enterprise edition availablecommercial infofree trial version availableOpen Source infoApache 2.0
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 languageGoNode.jsC++ and CUDAC++Scala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
OS X
LinuxAIX
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freedynamic schemayesyesyes
Typing infopredefined data types such as float or datenoyes infoJSON data typesyesyesyes
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 indexesnoyesnoyesno
SQL infoSupport of SQLnoSQL-like data manipulation statementsyesyesSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Thrift
Vega
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.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
All languages supporting JDBC/ODBC/Thrift
Python
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoCustom Functions infosince release 3.1nonono
Triggersyes, watching key changesnononono
Partitioning methods infoMethods for storing different data on different nodesA table resides as a whole on one (or more) nodes in a clusterSharding infoRound robinhorizontal partitioningyes, 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 infothe nodes on which a table resides can be definedMulti-source replicationnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of specific operationsnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlnoAccess rights for users and rolesfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardno

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More resources
etcdHarperDBHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Sadas EngineSpark SQL
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