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DBMS > etcd vs. Google Cloud Datastore vs. InfinityDB vs. Sadas Engine vs. Spark SQL

System Properties Comparison etcd vs. Google Cloud Datastore vs. InfinityDB vs. Sadas Engine vs. Spark SQL

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfinityDB  Xexclude from comparisonSadas Engine  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionA distributed reliable key-value storeAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA 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 storeKey-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score4.47
Rank#76  Overall
#12  Document stores
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
cloud.google.com/­datastoreboilerbay.comwww.sadasengine.comspark.apache.org/­sql
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
cloud.google.com/­datastore/­docsboilerbay.com/­infinitydb/­manualwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleBoiler Bay Inc.SADAS s.r.l.Apache Software Foundation
Initial release2008200220062014
Current release3.4, August 20194.08.03.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infofree trial version availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaC++Scala
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedAll 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 datenoyes, details hereyes 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.nonononono
Secondary indexesnoyesno infomanual creation possible, using inversions based on multi-value capabilityyesno
SQL infoSupport of SQLnoSQL-like query language (GQL)noyesSQL-like DML and DDL statements
APIs and other access methodsgRPC
JSON over HTTP
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
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
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java.Net
C
C#
C++
Groovy
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnousing Google App Enginenonono
Triggersyes, watching key changesCallbacks using the Google Apps Enginenonono
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 using Paxosnonenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsno infomanual creation possible, using inversions based on multi-value capabilityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID 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.nononoyes infomanaged by 'Learn by Usage'no
User concepts infoAccess controlnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)noAccess rights for users, groups and roles according to SQL-standardno

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More resources
etcdGoogle Cloud DatastoreInfinityDBSadas EngineSpark SQL
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