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

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

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
Name	EventStoreDB  Xexclude from comparison	Google Cloud Bigtable  Xexclude from comparison	IBM Db2 Event Store  Xexclude from comparison	Transwarp ArgoDB  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	Distributed Analytical Database to replace Hadoop+MPP hybrid architecture
Primary database model	Event Store	Key-value store Wide column store	Event Store Time Series DBMS	Relational DBMS
Secondary database models				Search engine
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 0.12 Rank #348   Overall #151   Relational DBMS
Website	www.eventstore.com	cloud.google.com/­bigtable	www.ibm.com/­products/­db2-event-store	www.transwarp.cn/­en/­product/­argodb
Technical documentation	developers.eventstore.com	cloud.google.com/­bigtable/­docs	www.ibm.com/­docs/­en/­db2-event-store	docs.transwarp.cn/­#/­documents-support/­docs?category=ARGODB
Developer	Event Store Limited	Google	IBM	Transwarp
Initial release	2012	2015	2017
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	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	yes
SQL Support of SQL		no	yes through the embedded Spark runtime	yes
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
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
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
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
Foreign keys Referential integrity		no	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data		Atomic single-row operations	no
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
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
More information provided by the system vendor We invite representatives of system vendors to contact us for updating and extending the system information, and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.
Related products and services We invite representatives of vendors of related products to contact us for presenting information about their offerings here.
More resources
	EventStoreDB	Google Cloud Bigtable	IBM Db2 Event Store	Transwarp ArgoDB
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

Share this page