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DBMS > Apache Impala vs. etcd vs. HarperDB vs. Sadas Engine vs. Spark SQL

System Properties Comparison Apache Impala vs. etcd vs. HarperDB vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonetcd  Xexclude from comparisonHarperDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA 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.SADAS 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 modelRelational DBMSKey-value storeDocument storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.55
Rank#248  Overall
#38  Document stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteimpala.apache.orgetcd.io
github.com/­etcd-io/­etcd
www.harperdb.iowww.sadasengine.comspark.apache.org/­sql
Technical documentationimpala.apache.org/­impala-docs.htmletcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.harperdb.io/­docswww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaHarperDBSADAS s.r.l.Apache Software Foundation
Initial release2013201720062014
Current release4.1.0, June 20223.4, August 20193.1, August 20218.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercial infofree community 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 languageC++GoNode.jsC++Scala
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
Linux
OS X
AIX
Linux
Windows
Linux
OS X
Windows
Data schemeyesschema-freedynamic schemayesyes
Typing infopredefined data types such as float or dateyesnoyes infoJSON data typesyesyes
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 indexesyesnoyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like data manipulation statementsyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
gRPC
JSON over HTTP
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
JDBC
ODBC
Proprietary protocol
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.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
.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoCustom Functions infosince release 3.1nono
Triggersnoyes, watching key changesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusterhorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes infothe nodes on which a table resides can be definednonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoAtomic execution of specific operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes, using LMDByesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess rights for users and rolesAccess rights for users, groups and roles according to SQL-standardno

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More resources
Apache ImpalaetcdHarperDBSadas EngineSpark SQL
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