DBMS > EventStoreDB vs. Google Cloud Bigtable vs. IBM Db2 Event Store vs. LeanXcale

System Properties Comparison EventStoreDB vs. Google Cloud Bigtable vs. IBM Db2 Event Store vs. LeanXcale

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Editorial information provided by DB-Engines
Name	EventStoreDB  Xexclude from comparison	Google Cloud Bigtable  Xexclude from comparison	IBM Db2 Event Store  Xexclude from comparison	LeanXcale  Xexclude from comparison
Description	Industrial-strength, open-source database solution built from the ground up for event sourcing.	Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.	Distributed Event Store optimized for Internet of Things use cases	A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities
Primary database model	Event Store	Key-value store Wide column store	Event Store Time Series DBMS	Key-value store Relational DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 1.19 Rank #173   Overall #1   Event Stores	Score 3.15 Rank #95   Overall #14   Key-value stores #8   Wide column stores	Score 0.27 Rank #309   Overall #2   Event Stores #28   Time Series DBMS	Score 0.36 Rank #280   Overall #40   Key-value stores #129   Relational DBMS
Website	www.eventstore.com	cloud.google.com/­bigtable	www.ibm.com/­products/­db2-event-store	www.leanxcale.com
Technical documentation	developers.eventstore.com	cloud.google.com/­bigtable/­docs	www.ibm.com/­docs/­en/­db2-event-store
Developer	Event Store Limited	Google	IBM	LeanXcale
Initial release	2012	2015	2017	2015
Current release	21.2, February 2021		2.0
License Commercial or Open Source	Open Source	commercial	commercial free developer edition available	commercial
Cloud-based only Only available as a cloud service	no	yes	no	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language			C and C++
Server operating systems	Linux Windows	hosted	Linux Linux, macOS, Windows for the developer addition
Data scheme		schema-free	yes	yes
Typing predefined data types such as float or date		no	yes
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
Secondary indexes		no	no
SQL Support of SQL		no	yes through the embedded Spark runtime	yes through Apache Derby
APIs and other access methods		gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java)	ADO.NET DB2 Connect JDBC ODBC RESTful HTTP API	JDBC Kafka Connector ODBC proprietary key/value interface Spark Connector
Supported programming languages		C# C++ Go Java JavaScript (Node.js) Python	C C# C++ Cobol Delphi Fortran Go Java JavaScript (Node.js) Perl PHP Python R Ruby Scala Visual Basic	C Java Scala
Server-side scripts Stored procedures		no	yes
Triggers		no	no
Partitioning methods Methods for storing different data on different nodes		Sharding	Sharding
Replication methods Methods for redundantly storing data on multiple nodes		Internal replication in Colossus, and regional replication between two clusters in different zones	Active-active shard replication
MapReduce Offers an API for user-defined Map/Reduce methods		yes	no	no
Consistency concepts Methods to ensure consistency in a distributed system		Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)	Eventual Consistency	Immediate Consistency
Foreign keys Referential integrity		no	no	yes
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data		Atomic single-row operations	no	ACID
Concurrency Support for concurrent manipulation of data		yes	No - written data is immutable	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
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.		no	yes	yes
User concepts Access control		Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)	fine grained access rights according to SQL-standard
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More resources
	EventStoreDB	Google Cloud Bigtable	IBM Db2 Event Store	LeanXcale
Recent citations in the news		Google's AI-First Strategy Brings Vector Support To Cloud Databases 1 March 2024, Forbes Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs 31 January 2022, InfoQ.com Google scales up Cloud Bigtable NoSQL database 27 January 2022, TechTarget Review: Google Bigtable scales with ease 7 September 2016, InfoWorld Google Launches Cloud Bigtable, A Highly Scalable And Performant NoSQL Database 6 May 2015, TechCrunch provided by Google 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

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