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DBMS > etcd vs. GigaSpaces vs. InfinityDB vs. Sadas Engine vs. Spark SQL

System Properties Comparison etcd vs. GigaSpaces vs. InfinityDB vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGigaSpaces  Xexclude from comparisonInfinityDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed reliable key-value storeHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA Java embedded Key-Value Store which extends the Java Map interfaceSADAS 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 store
Object oriented DBMS infoValues are user defined objects
Key-value storeRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.00
Rank#378  Overall
#57  Key-value stores
Score0.00
Rank#383  Overall
#158  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.gigaspaces.comboilerbay.comwww.sadasengine.comspark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.gigaspaces.com/­latest/­landing.htmlboilerbay.com/­infinitydb/­manualwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGigaspaces TechnologiesBoiler Bay Inc.SADAS s.r.l.Apache Software Foundation
Initial release2000200220062014
Current release3.4, August 201915.5, September 20204.08.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial licenses availablecommercialcommercial 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 languageGoJava, C++, .NetJavaC++Scala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
macOS
Solaris
Windows
All OS with a Java VMAIX
Linux
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesyes
Typing infopredefined data types such as float or datenoyesyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes
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.nono infoXML can be used for describing objects metadatanonono
Secondary indexesnoyesno infomanual creation possible, using inversions based on multi-value capabilityyesno
SQL infoSupport of SQLnoSQL-99 for query and DML statementsnoyesSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
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++
Java
Python
Scala
Java.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnonono
Triggersyes, watching key changesyes, event driven architecturenonono
Partitioning methods infoMethods for storing different data on different nodesShardingnonehorizontal 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.Multi-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
nonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integritynonono infomanual creation possible, using inversions based on multi-value capabilityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoOptimistic locking for transactions; no isolation for bulk loadsno
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.noyesnoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlnoRole-based access controlnoAccess rights for users, groups and roles according to SQL-standardno

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More resources
etcdGigaSpacesInfinityDBSadas EngineSpark SQL
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