DBMS > Dgraph vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. Tarantool vs. Vertica
System Properties Comparison Dgraph vs. Google Cloud Bigtable vs. Microsoft Azure Data Explorer vs. Tarantool vs. Vertica
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Name | Dgraph Xexclude from comparison | Google Cloud Bigtable Xexclude from comparison | Microsoft Azure Data Explorer Xexclude from comparison | Tarantool Xexclude from comparison | Vertica OpenText™ Vertica™ Xexclude from comparison | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Description | Distributed and scalable native Graph DBMS | Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail. | Fully managed big data interactive analytics platform | In-memory computing platform with a flexible data schema for efficiently building high-performance applications | 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 | Graph DBMS | Key-value store Wide column store | Relational DBMS column oriented | Document store Key-value store Relational DBMS | Relational DBMS Column oriented | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary database models | Document store If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell Event Store this is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps) Spatial DBMS Search engine support for complex search expressions docs.microsoft.com/en-us/azure/kusto/query/parseoperator FTS, Geospatial docs.microsoft.com/en-us/azure/kusto/query/geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine Time Series DBMS see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis | Spatial DBMS with Tarantool/GIS extension | Spatial DBMS Time Series DBMS | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Website | dgraph.io | cloud.google.com/bigtable | azure.microsoft.com/services/data-explorer | www.tarantool.io | www.vertica.com | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Technical documentation | dgraph.io/docs | cloud.google.com/bigtable/docs | docs.microsoft.com/en-us/azure/data-explorer | www.tarantool.io/en/doc | vertica.com/documentation | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Developer | Dgraph Labs, Inc. | Microsoft | VK | OpenText previously Micro Focus and Hewlett Packard | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Initial release | 2016 | 2015 | 2019 | 2008 | 2005 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Current release | cloud service with continuous releases | 2.10.0, May 2022 | 12.0.3, January 2023 | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
License Commercial or Open Source | Open Source Apache 2.0 | commercial | commercial | Open Source BSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise | commercial Limited community edition free | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Cloud-based only Only available as a cloud service | no | yes | yes | no | no on-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Implementation language | Go | C and C++ | C++ | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server operating systems | Linux OS X Windows | hosted | hosted | BSD Linux macOS | Linux | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Data scheme | schema-free | schema-free | Fixed schema with schema-less datatypes (dynamic) | Flexible data schema: relational definition for tables with ability to store json-like documents in columns | 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 | no | yes bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types | string, double, decimal, uuid, integer, blob, boolean, datetime | 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 | yes | no | no | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Secondary indexes | yes | no | all fields are automatically indexed | yes | No Indexes Required. Different internal optimization strategy, but same functionality included. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
SQL Support of SQL | no | no | Kusto Query Language (KQL), SQL subset | Full-featured ANSI SQL support | Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
APIs and other access methods | GraphQL query language gRPC (using protocol buffers) API HTTP API | gRPC (using protocol buffers) API HappyBase (Python library) HBase compatible API (Java) | Microsoft SQL Server communication protocol (MS-TDS) RESTful HTTP API | Open binary protocol | ADO.NET JDBC Kafka Connector ODBC RESTful HTTP API Spark Connector vSQL character-based, interactive, front-end utility | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Supported programming languages | C# C++ Go Java JavaScript (Node.js) PHP Python Ruby | C# C++ Go Java JavaScript (Node.js) Python | .Net Go Java JavaScript (Node.js) PowerShell Python R | C C# C++ Erlang Go Java JavaScript Lua Perl PHP Python Rust | C# C++ Go Java JavaScript (Node.js) Perl PHP Python R | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Server-side scripts Stored procedures | no | no | Yes, possible languages: KQL, Python, R | Lua, C and SQL stored procedures | yes, PostgreSQL PL/pgSQL, with minor differences | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Triggers | no | no | yes see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy | yes, before/after data modification events, on replication events, client session events | yes, called Custom Alerts | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Partitioning methods Methods for storing different data on different nodes | yes | Sharding | Sharding Implicit feature of the cloud service | Sharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime. | horizontal partitioning, hierarchical partitioning | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Replication methods Methods for redundantly storing data on multiple nodes | Synchronous replication via Raft | Internal replication in Colossus, and regional replication between two clusters in different zones | yes Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant. | Asynchronous replication with multi-master option Configurable replication topology (full-mesh, chain, star) Synchronous quorum replication (with Raft) | 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 | no | yes | Spark connector (open source): github.com/Azure/azure-kusto-spark | no Bi-directional Spark integration | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Consistency concepts Methods to ensure consistency in a distributed system | Immediate Consistency | Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters) | Eventual Consistency Immediate Consistency | Casual consistency across sharding partitions Eventual consistency within replicaset partition when using asyncronous replication Immediate Consistency within single instance Sequential consistency including linearizable read within replicaset partition when using Raft | Immediate Consistency | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Foreign keys Referential integrity | no | no | no | yes | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data | ACID | Atomic single-row operations | no | ACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions | ACID | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Concurrency Support for concurrent manipulation of data | yes | yes | yes | yes, cooperative multitasking | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Durability Support for making data persistent | yes | yes | yes | yes, write ahead logging | yes | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
In-memory capabilities Is there an option to define some or all structures to be held in-memory only. | no | no | yes, full featured in-memory storage engine with persistence | no | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
User concepts Access control | no Planned for future releases | Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM) | Azure Active Directory Authentication | Access Control Lists Mutual TLS authentication for Tarantol Enterprise Password based authentication Role-based access control (RBAC) and LDAP for Tarantol Enterprise Users and Roles | fine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Dgraph | Google Cloud Bigtable | Microsoft Azure Data Explorer | Tarantool | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Specific characteristics | Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Competitive advantages | Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Typical application scenarios | Communication and network analytics, Embedded analytics, Fraud monitoring and Risk... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Key customers | Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Licensing and pricing models | Cost-based models and subscription-based models are both available. One license is... » more | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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Dgraph | Google Cloud Bigtable | Microsoft Azure Data Explorer | Tarantool | Vertica OpenText™ Vertica™ | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
DB-Engines blog posts | Data processing speed and reliability: in-memory synchronous replication | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
Recent citations in the news | Dgraph on AWS: Setting up a horizontally scalable graph database | Amazon Web Services Popular Open Source GraphQL Company Dgraph Secures $6M in Seed Round with New Leadership Dgraph launches Slash GraphQL, a GraphQL-native database Backend-as-a-Service Dgraph Raises $6M in Seed Funding Dgraph Rises to the Top Graph Database on GitHub With 11 G2 Badges and 11M Downloads provided by Google News | Google's AI-First Strategy Brings Vector Support To Cloud Databases Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs Google scales up Cloud Bigtable NoSQL database Review: Google Bigtable scales with ease Google Cloud makes it cheaper to run smaller workloads on Bigtable provided by Google News | We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates Update records in a Kusto Database (public preview) Public Preview: Azure Data Explorer connector for Apache Flink Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ... New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates provided by Google News | Tarantool Announces New Enterprise Version With Enhanced Scaling and Monitoring Capabilities Deploying Tarantool Cartridge applications with zero effort (Part 1) VShard — horizontal scaling in Tarantool Accelerating PHP connectors for Tarantool using Async, Swoole, and Parallel provided by Google News | 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 Querying a Vertica data source in Amazon Athena using the Athena Federated Query SDK | Amazon Web Services Postgres pioneer Michael Stonebraker promises to upend the database once more provided by Google News |
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