DBMS > GreptimeDB vs. IBM Db2 Event Store vs. Microsoft SQL Server vs. XTDB

System Properties Comparison GreptimeDB vs. IBM Db2 Event Store vs. Microsoft SQL Server vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Distributed Event Store optimized for Internet of Things use cases

Microsofts flagship relational DBMS

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Time Series DBMS

Event Store
Time Series DBMS

Relational DBMS

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.09
Rank	#343	Overall
	#31	Time Series DBMS

Score	0.18
Rank	#315	Overall
	#2	Event Stores
	#26	Time Series DBMS

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	0.13
Rank	#330	Overall
	#45	Document stores

Website

greptime.com

www.ibm.com/products/db2-event-store

www.microsoft.com/en-us/sql-server

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

docs.greptime.com

www.ibm.com/docs/en/db2-event-store

learn.microsoft.com/en-US/sql/sql-server

www.xtdb.com/docs

Developer

Greptime Inc.

IBM

Microsoft

Juxt Ltd.

Initial release

2022

2017

1989

2019

Current release

2.0

SQL Server 2022, November 2022

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

free developer edition available

commercial

restricted free version is available

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

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Implementation language

Rust

C and C++

C++

Clojure

Server operating systems

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free, schema definition possible

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

gRPC
HTTP API
JDBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST
JDBC

Supported programming languages

C++
Erlang
Go
Java
JavaScript

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Clojure
Java

Server-side scripts

Stored procedures

Python

yes

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

tables can be distributed across several files (horizontal partitioning); sharding through federation

none

Replication methods

Methods for redundantly storing data on multiple nodes

Active-active shard replication

yes, but depending on the SQL-Server Edition

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

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

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Simple rights management via user accounts

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
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