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DBMS > EsgynDB vs. GeoSpock vs. LevelDB vs. Microsoft Azure Cosmos DB vs. Splice Machine

System Properties Comparison EsgynDB vs. GeoSpock vs. LevelDB vs. Microsoft Azure Cosmos DB vs. Splice Machine

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonGeoSpock  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionSpatial and temporal data processing engine for extreme data scaleEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesGlobally distributed, horizontally scalable, multi-model database serviceOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSRelational DBMSKey-value storeDocument store
Graph DBMS
Key-value store
Wide column store
Relational DBMS
Secondary database modelsTime Series DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.26
Rank#311  Overall
#141  Relational DBMS
Score3.32
Rank#100  Overall
#16  Key-value stores
Score30.39
Rank#27  Overall
#4  Document stores
#2  Graph DBMS
#3  Key-value stores
#3  Wide column stores
Score0.54
Rank#257  Overall
#118  Relational DBMS
Websitewww.esgyn.cngeospock.comgithub.com/­google/­leveldbazure.microsoft.com/­services/­cosmos-dbsplicemachine.com
Technical documentationgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mdlearn.microsoft.com/­azure/­cosmos-dbsplicemachine.com/­how-it-works
DeveloperEsgynGeoSpockGoogleMicrosoftSplice Machine
Initial release2015201120142014
Current release2.0, September 20191.23, February 20213.1, March 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSDcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaJava, JavascriptC++Java
Server operating systemsLinuxhostedIllumos
Linux
OS X
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeyesyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes infoJSON typesyes
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.nonono
Secondary indexesyestemporal, categoricalnoyes infoAll properties auto-indexed by defaultyes
SQL infoSupport of SQLyesANSI SQL for query only (using Presto)noSQL-like query languageyes
APIs and other access methodsADO.NET
JDBC
ODBC
JDBCDocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetC++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresJava Stored ProceduresnonoJavaScriptyes infoJava
TriggersnononoJavaScriptyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardingnoneSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersnoneyes infoImplicit feature of the cloud serviceMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonowith Hadoop integration infoIntegration with Hadoop/HDInsight on Azure*Yes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyBounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency infoConsistency level configurable on request level
Session Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoMulti-item ACID transactions with snapshot isolation within a partitionACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes infowith automatic compression on writesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users can be defined per tablenoAccess rights can be defined down to the item levelAccess rights for users, groups and roles according to SQL-standard

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More resources
EsgynDBGeoSpockLevelDBMicrosoft Azure Cosmos DB infoformer name was Azure DocumentDBSplice Machine
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