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DBMS > GigaSpaces vs. HarperDB vs. LMDB vs. Microsoft Azure Synapse Analytics vs. WakandaDB

System Properties Comparison GigaSpaces vs. HarperDB vs. LMDB vs. Microsoft Azure Synapse Analytics vs. WakandaDB

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonHarperDB  Xexclude from comparisonLMDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsUltra-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.A high performant, light-weight, embedded key-value database libraryElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Document storeKey-value storeRelational DBMSObject oriented DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score0.55
Rank#248  Overall
#38  Document stores
Score1.99
Rank#125  Overall
#21  Key-value stores
Score20.56
Rank#31  Overall
#19  Relational DBMS
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitewww.gigaspaces.comwww.harperdb.iowww.symas.com/­symas-embedded-database-lmdbazure.microsoft.com/­services/­synapse-analyticswakanda.github.io
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.harperdb.io/­docswww.lmdb.tech/­docdocs.microsoft.com/­azure/­synapse-analyticswakanda.github.io/­doc
DeveloperGigaspaces TechnologiesHarperDBSymasMicrosoftWakanda SAS
Initial release20002017201120162012
Current release15.5, September 20203.1, August 20210.9.32, January 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availablecommercial infofree community edition availableOpen SourcecommercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, C++, .NetNode.jsCC++C++, JavaScript
Server operating systemsLinux
macOS
Solaris
Windows
Linux
OS X
Linux
Unix
Windows
hostedLinux
OS X
Windows
Data schemeschema-freedynamic schemaschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes 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.no infoXML can be used for describing objects metadatanononono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLSQL-99 for query and DML statementsSQL-like data manipulation statementsnoyesno
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
C++
Java
Python
Scala
.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++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
C#
Java
PHP
JavaScript
Server-side scripts infoStored proceduresyesCustom Functions infosince release 3.1noTransact SQLyes
Triggersyes, event driven architecturenononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingA table resides as a whole on one (or more) nodes in a clusternoneSharding, horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infothe nodes on which a table resides can be definednoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDAtomic execution of specific operationsACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes, using LMDByesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlRole-based access controlAccess rights for users and rolesnoyesyes

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More resources
GigaSpacesHarperDBLMDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseWakandaDB
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