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DBMS > Firebase Realtime Database vs. IBM Db2 Event Store vs. LMDB vs. Microsoft Azure Synapse Analytics vs. WakandaDB

System Properties Comparison Firebase Realtime Database vs. IBM Db2 Event Store vs. LMDB vs. Microsoft Azure Synapse Analytics vs. WakandaDB

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonLMDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonWakandaDB  Xexclude from comparison
DescriptionCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Distributed Event Store optimized for Internet of Things use casesA 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 storeEvent Store
Time Series DBMS
Key-value storeRelational DBMSObject oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.07
Rank#38  Overall
#6  Document stores
Score0.25
Rank#320  Overall
#2  Event Stores
#28  Time Series DBMS
Score2.62
Rank#117  Overall
#21  Key-value stores
Score23.95
Rank#30  Overall
#18  Relational DBMS
Score0.06
Rank#374  Overall
#17  Object oriented DBMS
Websitefirebase.google.com/­products/­realtime-databasewww.ibm.com/­products/­db2-event-storewww.symas.com/­symas-embedded-database-lmdbazure.microsoft.com/­services/­synapse-analyticswakanda.github.io
Technical documentationfirebase.google.com/­docs/­databasewww.ibm.com/­docs/­en/­db2-event-storewww.lmdb.tech/­docdocs.microsoft.com/­azure/­synapse-analyticswakanda.github.io/­doc
DeveloperGoogle infoacquired by Google 2014IBMSymasMicrosoftWakanda SAS
Initial release20122017201120162012
Current release2.00.9.32, January 20242.7.0 (April 29, 2019), April 2019
License infoCommercial or Open Sourcecommercialcommercial infofree developer edition availableOpen SourcecommercialOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++CC++C++, JavaScript
Server operating systemshostedLinux infoLinux, macOS, Windows for the developer additionLinux
Unix
Windows
hostedLinux
OS X
Windows
Data schemeschema-freeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesnonoyes
SQL infoSupport of SQLnoyes infothrough the embedded Spark runtimenoyesno
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
RESTful HTTP API
Supported programming languagesJava
JavaScript
Objective-C
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
.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 procedureslimited functionality with using 'rules'yesnoTransact SQLyes
TriggersCallbacks are triggered when data changesnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding, horizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesActive-active shard replicationnoneyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual 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 datayesnoACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlyes, based on authentication and database rulesfine grained access rights according to SQL-standardnoyesyes

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More resources
Firebase Realtime DatabaseIBM Db2 Event StoreLMDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseWakandaDB
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