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DBMS > EJDB vs. Geode vs. Google Cloud Datastore vs. Kinetica vs. LevelDB

System Properties Comparison EJDB vs. Geode vs. Google Cloud Datastore vs. Kinetica vs. LevelDB

Editorial information provided by DB-Engines
NameEJDB  Xexclude from comparisonGeode  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonKinetica  Xexclude from comparisonLevelDB  Xexclude from comparison
DescriptionEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Geode is a distributed data container, pooling memory, CPU, network resources, and optionally local disk across multiple processesAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformFully vectorized database across both GPUs and CPUsEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string values
Primary database modelDocument storeKey-value storeDocument storeRelational DBMSKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.13
Rank#331  Overall
#46  Document stores
Score1.51
Rank#147  Overall
#25  Key-value stores
Score4.13
Rank#71  Overall
#12  Document stores
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score2.33
Rank#111  Overall
#19  Key-value stores
Websitegithub.com/­Softmotions/­ejdbgeode.apache.orgcloud.google.com/­datastorewww.kinetica.comgithub.com/­google/­leveldb
Technical documentationgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdgeode.apache.org/­docscloud.google.com/­datastore/­docsdocs.kinetica.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperSoftmotionsOriginally developed by Gemstone. They outsourced the project to Apache in 2015 but still deliver a commercial version as Gemfire.GoogleKineticaGoogle
Initial release20122002200820122011
Current release1.1, February 20177.1, August 20211.23, February 2021
License infoCommercial or Open SourceOpen Source infoGPLv2Open Source infoApache Version 2; commercial licenses available as GemfirecommercialcommercialOpen Source infoBSD
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJavaC, C++C++
Server operating systemsserver-lessAll OS with a Java VM infothe JDK (8 or later) is also requiredhostedLinuxIllumos
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyes infostring, integer, double, bool, date, object_idyesyes, details hereyesno
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.nononono
Secondary indexesnonoyesyesno
SQL infoSupport of SQLnoSQL-like query language (OQL)SQL-like query language (GQL)SQL-like DML and DDL statementsno
APIs and other access methodsin-process shared libraryJava Client API
Memcached protocol
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesActionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
.Net
All JVM based languages
C++
Groovy
Java
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Server-side scripts infoStored proceduresnouser defined functionsusing Google App Engineuser defined functionsno
Triggersnoyes infoCache Event ListenersCallbacks using the Google Apps Engineyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationMulti-source replication using PaxosSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityno infotypically not needed, however similar functionality with collection joins possiblenoyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyes, on a single nodeACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsnono
Concurrency infoSupport for concurrent manipulation of datayes infoRead/Write Lockingyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infowith automatic compression on writes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoGPU vRAM or System RAM
User concepts infoAccess controlnoAccess rights per client and object definableAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Access rights for users and roles on table levelno

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More resources
EJDBGeodeGoogle Cloud DatastoreKineticaLevelDB
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