DBMS > Cassandra vs. Google Cloud Spanner vs. InfluxDB vs. Oracle Berkeley DB vs. Vertica
System Properties Comparison Cassandra vs. Google Cloud Spanner vs. InfluxDB vs. Oracle Berkeley DB vs. Vertica
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Name | Cassandra Xexclude from comparison | Google Cloud Spanner Xexclude from comparison | InfluxDB Xexclude from comparison | Oracle Berkeley DB Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Wide-column store based on ideas of BigTable and DynamoDB Optimized for write access | A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play. | DBMS for storing time series, events and metrics | Widely used in-process key-value store | Cloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Primary database model | Wide column store | Relational DBMS | Time Series DBMS | Key-value store supports sorted and unsorted key sets Native XML DBMS in the Oracle Berkeley DB XML version | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Vector DBMS starting with release V5 | Spatial DBMS with GEO package | Spatial DBMS Time Series DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | cassandra.apache.org | cloud.google.com/spanner | www.influxdata.com/products/influxdb-overview | www.oracle.com/database/technologies/related/berkeleydb.html | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | cassandra.apache.org/doc/latest | cloud.google.com/spanner/docs | docs.influxdata.com/influxdb | docs.oracle.com/cd/E17076_05/html/index.html | vertica.com/documentation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Apache Software Foundation Apache top level project, originally developped by Facebook | Oracle originally developed by Sleepycat, which was acquired by Oracle | OpenText previously Micro Focus and Hewlett Packard | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2008 | 2017 | 2013 | 1994 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | 4.1.3, July 2023 | 2.7.6, April 2024 | 18.1.40, May 2020 | 12.0.3, January 2023 | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache version 2 | commercial | Open Source MIT-License; commercial enterprise version available | Open Source commercial license available | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | no | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed. | Astra DB: Multi-cloud DBaaS built on Apache Cassandra. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Implementation language | Java | Go | C, Java, C++ (depending on the Berkeley DB edition) | C++ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | BSD Linux OS X Windows | hosted | Linux OS X through Homebrew | AIX Android FreeBSD iOS Linux OS X Solaris VxWorks Windows | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | yes | schema-free | schema-free | Yes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typing predefined data types such as float or date | yes | yes | Numeric data and Strings | 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 | yes only with the Berkeley DB XML edition | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | restricted only equality queries, not always the best performing solution | yes | no | yes | No Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | SQL-like SELECT, DML and DDL statements (CQL) | yes Query statements complying to ANSI 2011 | SQL-like query language | yes SQL interfaced based on SQLite is available | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | Proprietary protocol CQL (Cassandra Query Language, an SQL-like language) Thrift | gRPC (using protocol buffers) API JDBC At present, JDBC supports read-only queries. No support for DDL or DML statements. RESTful HTTP API | HTTP API JSON over UDP | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# C++ Clojure Erlang Go Haskell Java JavaScript Node.js Perl PHP Python Ruby Scala | Go Java JavaScript (Node.js) Python | .Net Clojure Erlang Go Haskell Java JavaScript JavaScript (Node.js) Lisp Perl PHP Python R Ruby Rust Scala | .Net Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET others Third-party libraries to manipulate Berkeley DB files are available for many languages C C# C++ Java JavaScript (Node.js) 3rd party binding Perl Python Tcl | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | no | no | no | yes, PostgreSQL PL/pgSQL, with minor differences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | yes | no | no | yes only for the SQL API | yes, called Custom Alerts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | Sharding no "single point of failure" | Sharding | Sharding in enterprise version only | none | horizontal partitioning, hierarchical partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | selectable replication factor Representation of geographical distribution of servers is possible | Multi-source replication with 3 replicas for regional instances. | selectable replication factor in enterprise version only | Source-replica replication | Multi-source replication One, or more copies of data replicated across nodes, or object-store used for repository. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
MapReduce Offers an API for user-defined Map/Reduce methods | yes | yes using Google Cloud Dataflow | no | no | no Bi-directional Spark integration | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Eventual Consistency Immediate Consistency can be individually decided for each write operation | Immediate Consistency | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | yes by using interleaved tables, this features focuses more on performance improvements than on referential integrity | no | no | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | no Atomicity and isolation are supported for single operations | ACID Strict serializable isolation | no | ACID | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | yes Depending on used storage engine | yes | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | Access rights for users can be defined per object | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | simple rights management via user accounts | no | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
More information provided by the system vendor | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cassandra | Google Cloud Spanner | InfluxDB | Oracle Berkeley DB | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Apache Cassandra is the leading NoSQL, distributed database management system, well... » more | InfluxData is the creator of InfluxDB , the open source time series database. It... » more | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | No single point of failure ensures 100% availability . Operational simplicity for... » more | Time to Value InfluxDB is available in all the popular languages and frameworks,... » more | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Internet of Things (IOT), fraud detection applications, recommendation engines, product... » more | IoT & Sensor Monitoring Developers are witnessing the instrumentation of every available... » more | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best... » more | InfluxData has more than 1,900 paying customers, including customers include MuleSoft,... » more | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Market metrics | Cassandra is used by 40% of the Fortune 100. » more | Fastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances » more | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Apache license Pricing for commercial distributions provided by DataStax and available... » more | Open source core with closed source clustering available either on-premise or on... » more | Cost-based models and subscription-based models are both available. One license is... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
News | An Introduction to David Jones-Gilardi, Developer Relations Introducing Tejas Kumar, Developer Relations Engineer Indexing All of Wikipedia on a Laptop An Introduction to Phil Nash, Developer Relations Focus on Creativity, Not Clusters: DataStax Mission Control in Action! | Scaling Data Collection: Solving Renewable Energy Challenges with InfluxDB Deadman Alerts with Grafana and InfluxDB Cloud 3.0 Chasing the Skies: Monitoring Flights with InfluxDB Monitoring Your Cloud Environments and Applications with InfluxDB Webinar Recap: Unleash the Full Potential of Your Time Series Data with InfluxDB and AWS | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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3rd parties | Cassandra Forward event: Want to level up your Cassandra game? Watch now replays of the March 2023 sessions. » more CData: Connect to Big Data & NoSQL through standard Drivers. » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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More resources | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cassandra | Google Cloud Spanner | InfluxDB | Oracle Berkeley DB | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Cassandra keeps climbing the ranks of the DB-Engines Ranking Oracle is the DBMS of the Year Winners, losers and an attractive newcomer in Novembers DB-Engines ranking | Why Build a Time Series Data Platform? Time Series DBMS are the database category with the fastest increase in popularity Time Series DBMS as a new trend? | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | ScyllaDB 6.0 advances open source database scalability Here's What to Know About Apache Cassandra 5.0 Microsoft extends life support for aging Apache Cassandra 3.11 database How Zalando migrated their shopping carts to Amazon DynamoDB from Apache Cassandra | Amazon Web Services Microsoft Build 2024: Cosmos DB for NoSQL gets vector search provided by Google News | Google Improves Cloud Spanner: More Compute and Storage without Price Increase Google turns up the heat on AWS, claims Cloud Spanner is half the cost of DynamoDB Google makes its Cloud Spanner database service faster and more cost-efficient Google Cloud just fired a major volley at AWS as the cloud wars heat up Google Spanner: When Do You Need to Move to It? provided by Google News | Amazon Timestream for InfluxDB is now generally available Amazon Timestream: Managed InfluxDB for Time Series Data Apache Doris for Log and Time Series Data Analysis in NetEase: Why Not Elasticsearch and InfluxDB? InfluxData Collaborating with AWS to Bring InfluxDB and Time Series Analytics to Developers Around the World How the FDAP Stack Gives InfluxDB 3.0 Real-Time Speed, Efficiency provided by Google News | Margo Seltzer Named ACM Athena Lecturer for Technical and Mentoring Contributions ACM recognizes far-reaching technical achievements with special awards Margo I. Seltzer | Berkman Klein Center Oracle buys Sleepycat Software Database Trends Report: SQL Beats NoSQL, MySQL Most Popular -- ADTmag provided by Google News | HP Rolls Out Vertica Marketplace for Big Data Analytics MapR Hadoop Upgrade Runs HP Vertica Stonebraker Seeks to Invert the Computing Paradigm with DBOS OpenText expands enterprise portfolio with AI and Micro Focus integrations Postgres pioneer Michael Stonebraker promises to upend the database once more provided by Google News |
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