DBMS > BigObject vs. IBM Db2 Event Store vs. Microsoft Azure Synapse Analytics vs. NSDb

System Properties Comparison BigObject vs. IBM Db2 Event Store vs. Microsoft Azure Synapse Analytics vs. NSDb

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Editorial information provided by DB-Engines
Name	BigObject  Xexclude from comparison	IBM Db2 Event Store  Xexclude from comparison	Microsoft Azure Synapse Analytics previously named Azure SQL Data Warehouse  Xexclude from comparison	NSDb  Xexclude from comparison
Description	Analytic DBMS for real-time computations and queries	Distributed Event Store optimized for Internet of Things use cases	Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server	Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database model	Relational DBMS a hierachical model (tree) can be imposed	Event Store Time Series DBMS	Relational DBMS	Time Series DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 0.19 Rank #329   Overall #146   Relational DBMS	Score 0.27 Rank #309   Overall #2   Event Stores #28   Time Series DBMS	Score 19.93 Rank #31   Overall #19   Relational DBMS	Score 0.08 Rank #369   Overall #40   Time Series DBMS
Website	bigobject.io	www.ibm.com/­products/­db2-event-store	azure.microsoft.com/­services/­synapse-analytics	nsdb.io
Technical documentation	docs.bigobject.io	www.ibm.com/­docs/­en/­db2-event-store	docs.microsoft.com/­azure/­synapse-analytics	nsdb.io/­Architecture
Developer	BigObject, Inc.	IBM	Microsoft
Initial release	2015	2017	2016	2017
Current release		2.0
License Commercial or Open Source	commercial free community edition available	commercial free developer edition available	commercial	Open Source Apache Version 2.0
Cloud-based only Only available as a cloud service	no	no	yes	no
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Implementation language		C and C++	C++	Java, Scala
Server operating systems	Linux distributed as a docker-image OS X distributed as a docker-image (boot2docker) Windows distributed as a docker-image (boot2docker)	Linux Linux, macOS, Windows for the developer addition	hosted	Linux macOS
Data scheme	yes	yes	yes
Typing predefined data types such as float or date	yes	yes	yes	yes: int, bigint, decimal, string
XML support Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.	no	no	no	no
Secondary indexes	yes	no	yes	all fields are automatically indexed
SQL Support of SQL	SQL-like DML and DDL statements	yes through the embedded Spark runtime	yes	SQL-like query language
APIs and other access methods	fluentd ODBC RESTful HTTP API	ADO.NET DB2 Connect JDBC ODBC RESTful HTTP API	ADO.NET JDBC ODBC	gRPC HTTP REST WebSocket
Supported programming languages		C C# C++ Cobol Delphi Fortran Go Java JavaScript (Node.js) Perl PHP Python R Ruby Scala Visual Basic	C# Java PHP	Java Scala
Server-side scripts Stored procedures	Lua	yes	Transact SQL	no
Triggers	no	no	no
Partitioning methods Methods for storing different data on different nodes	none	Sharding	Sharding, horizontal partitioning	Sharding
Replication methods Methods for redundantly storing data on multiple nodes	none	Active-active shard replication	yes
MapReduce Offers an API for user-defined Map/Reduce methods	no	no	no	no
Consistency concepts Methods to ensure consistency in a distributed system	none	Eventual Consistency	Immediate Consistency	Eventual Consistency
Foreign keys Referential integrity	yes automatically between fact table and dimension tables	no	no docs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	no	no	ACID	no
Concurrency Support for concurrent manipulation of data	yes Read/write lock on objects (tables, trees)	No - written data is immutable	yes	yes
Durability Support for making data persistent	yes	Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage	yes	Using Apache Lucene
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	yes
User concepts Access control	no	fine grained access rights according to SQL-standard	yes
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More resources
	BigObject	IBM Db2 Event Store	Microsoft Azure Synapse Analytics previously named Azure SQL Data Warehouse	NSDb
Recent citations in the news		Advancements in streaming data storage, real-time analysis and machine learning 25 July 2019, IBM How IBM Is Turning Db2 into an 'AI Database' 3 June 2019, Datanami Best cloud databases of 2022 4 October 2022, ITPro Why a robust data management strategy is essential today | IBM HDM 19 September 2019, Express Computer provided by Google News	General Available: Azure Synapse Runtime for Apache Spark 3.4 is now GA | Azure updates 8 April 2024, Microsoft Azure Synapse Runtime for Apache Spark 3.2 End of Support | Azure updates 22 March 2024, Microsoft Azure Synapse Analytics: Everything you need to know about Microsoft's cloud analytics platform 24 September 2023, DataScientest Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT | Amazon Web Services 18 October 2023, AWS Blog Azure Synapse vs. Databricks: Data Platform Comparison 2024 26 March 2024, eWeek provided by Google News

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