DBMS > BigObject vs. EventStoreDB vs. Google Cloud Bigtable vs. Microsoft Azure Synapse Analytics

System Properties Comparison BigObject vs. EventStoreDB vs. Google Cloud Bigtable vs. Microsoft Azure Synapse Analytics

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
Name	BigObject  Xexclude from comparison	EventStoreDB  Xexclude from comparison	Google Cloud Bigtable  Xexclude from comparison	Microsoft Azure Synapse Analytics previously named Azure SQL Data Warehouse  Xexclude from comparison
Description	Analytic DBMS for real-time computations and queries	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.	Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database model	Relational DBMS a hierachical model (tree) can be imposed	Event Store	Key-value store Wide column store	Relational DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart	Score 0.19 Rank #329   Overall #146   Relational DBMS	Score 1.19 Rank #173   Overall #1   Event Stores	Score 3.15 Rank #95   Overall #14   Key-value stores #8   Wide column stores	Score 19.93 Rank #31   Overall #19   Relational DBMS
Website	bigobject.io	www.eventstore.com	cloud.google.com/­bigtable	azure.microsoft.com/­services/­synapse-analytics
Technical documentation	docs.bigobject.io	developers.eventstore.com	cloud.google.com/­bigtable/­docs	docs.microsoft.com/­azure/­synapse-analytics
Developer	BigObject, Inc.	Event Store Limited	Google	Microsoft
Initial release	2015	2012	2015	2016
Current release		21.2, February 2021
License Commercial or Open Source	commercial free community edition available	Open Source	commercial	commercial
Cloud-based only Only available as a cloud service	no	no	yes	yes
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language				C++
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 Windows	hosted	hosted
Data scheme	yes		schema-free	yes
Typing predefined data types such as float or date	yes		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	no
Secondary indexes	yes		no	yes
SQL Support of SQL	SQL-like DML and DDL statements		no	yes
APIs and other access methods	fluentd ODBC RESTful HTTP API		gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java)	ADO.NET JDBC ODBC
Supported programming languages			C# C++ Go Java JavaScript (Node.js) Python	C# Java PHP
Server-side scripts Stored procedures	Lua		no	Transact SQL
Triggers	no		no	no
Partitioning methods Methods for storing different data on different nodes	none		Sharding	Sharding, horizontal partitioning
Replication methods Methods for redundantly storing data on multiple nodes	none		Internal replication in Colossus, and regional replication between two clusters in different zones	yes
MapReduce Offers an API for user-defined Map/Reduce methods	no		yes	no
Consistency concepts Methods to ensure consistency in a distributed system	none		Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)	Immediate 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
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	no		Atomic single-row operations	ACID
Concurrency Support for concurrent manipulation of data	yes Read/write lock on objects (tables, trees)		yes	yes
Durability Support for making data persistent	yes		yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes		no
User concepts Access control	no		Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)	yes
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
	BigObject	EventStoreDB	Google Cloud Bigtable	Microsoft Azure Synapse Analytics previously named Azure SQL Data Warehouse
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 Cloud makes it cheaper to run smaller workloads on Bigtable 7 April 2020, TechCrunch 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 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 Runtime for Apache Spark 3.2 End of Support | Azure updates 22 March 2024, Microsoft Azure Synapse vs. Databricks: Data Platform Comparison 2024 26 March 2024, eWeek provided by Google News

Share this page